Medical researchers develop new methodology for molecular mechanisms of disease
By Andy Flick, Evolutionary Studies Initiative scientific coordinator
Evolutionary Studies Initiative researcher Eric Gamazon and his former postdoctoral researcher, Dan Zhou (now faculty at Zhejiang University), recently published new software and methodology for understanding the molecular basis of disease. They then applied their work to understanding the genetic basis for COVID-19 severity. The study is published in npj Genomic Medicine.
According to Zhou, “we developed a novel framework and metrics to evaluate the contribution of a genomic segment of interest to phenotypic variation.”
The pair then identified a specific phenotype to test their new method. They chose COVID-19 severity as their phenotype and used differences among individuals as the variation.
“We applied our method to the host genetics of COVID-19 severity. In this case, the most significant association with the disease phenotype is a locus that contains a 49.4 Kb introgressed DNA segment from an archaic Neanderthal genome,” Gamazon said.
Genes that humans inherited from the Neanderthal genome may inform who gets severely ill during a bout of novel coronavirus. Specifically, they found a correlation between severe disease symptoms like inflammation and disturbances in smell and taste with archaic genes located on chromosome 3. In other words, people who carry these genes inherited from Neanderthals are at higher risk to develop severe COVID-19 symptoms.
One feature key to this research was BioVU, a repository of DNA from clinical tests using blood housed at Vanderbilt. BioVU contains hundreds of thousands of samples that have been de-identified for research use.
According to Gamazon, “a large-scale electronic health records linked biobank such as BioVU provides a platform to investigate the effect of genes on potential complications.”
Gamazon concluded, “we hope that our new method will prove useful in helping future researchers identify relevant genes for other complex diseases. We hope that this computational tool will be used to generate new insights into molecular mechanisms of disease.”
Zhou felt a strong sense of personal growth in the Gamazon lab, noting that the lab was inclusive of folks from all sorts of different backgrounds.
“People joined the lab from a variety of backgrounds, including human genetics, neuroscience, computer science, physics, molecular biology, pathology, epidemiology, etc. This diversity was fantastic for generating ideas and ways of solving scientific problems,” Zhou said.
Funding Statement: This research is supported by the National Institutes of Health (NIH) Genomic Innovator Award R35HG010718, NIH/NHGRI R01HG011138, NIH/NIA AG068026, and NIH/NIGMS R01GM140287.
Citation: Zhou, D., Gamazon, E.R. Integrative transcriptomic, evolutionary, and causal inference framework for region-level analysis: Application to COVID-19. npj Genom. Med. 7, 24 (2022). https://doi.org/10.1038/s41525-022-00296-y