Spotlight on Population Genetics: Targeting Variants for Drug Discovery and Development
After receiving my PhD in bioinformatics, I was a postdoc at Cold Spring Harbor Laboratory, where I developed a method to help identify which regions of the human genome are most resistant to mutations. To identify these functional regions, we used genome sequence data sampled from tens of thousands of humans.
I have always thought of population genetics as a sort of archeology — without the physical ancient artifacts, without the big dig sites, but full of fascinating information about the history of humans lying just beneath the surface. This is information that can lead us to understand more about the environments a given population lived in, the food they ate, how they moved around, and how they interacted with different populations.
In the field of population genetics, we look at the genetics of populations as a whole rather than focusing on an individual’s genetic traits. More specifically, in my work at Variant Bio, I apply and develop methods to identify genomic variants that have potentially been beneficial to human populations living in diverse environments or with unique populations histories. I then test whether these genomic variants, or variants close to them, are correlated with any interesting clinical measurements, such as incidence of disease or measures of metabolism.
I am most focused on developing methods for selection boosted Genome-Wide Association Studies, or sbGWAS. GWAS refers to a research approach used to identify genomic variants that are statistically associated with a risk for a disease or a particular trait. The National Human Genome Research Institute says it best: the goal of a GWAS “is to screen the entire genome of large numbers of individuals to look for associations between millions of genetic variants within those individuals and their disease outcomes or sometimes for associations between the variants and non-disease trait.”
We have recently applied this method to identify positively selected variants that are also associated with disease in populations of French Polynesia, Aotearoa New Zealand, Uganda, and South Africa. Phenotypes we measure include various enzymes, morphological characteristics, amino acid levels, and other measures that are often used by physicians to diagnose and evaluate patients’ disease status.
I am looking for variants that are uniquely beneficial to populations that have undergone adaptive events. Some of these variants may be involved in disease pathways, which can be learned by testing their correlations to various phenotypes. Conventional GWAS typically have a higher threshold for significance, as the whole genome is tested. By reducing the tested region to positively selected regions we reduce the significance threshold allowing potential associations that would not be significant with conventional GWAS to be identified. For example, in a study in Aotearoa New Zealand we were able to increase the number of associations found by 139 percent when including analysis done with sbGWAS. Targeting these variants could lead to the development of life-saving therapies.
When Variant Bio is deciding on a new project, the population genetics team plays a critical role. Our findings inform project design, including choice of reference populations, and numbers of individuals to sample. The results from our analysis are sent to our research and development team in the form of gene/variants lists, which are then investigated more thoroughly for their potentials as drug targets.
One of the things I’m most excited about in my work as a population geneticist is the fact that every day, we are helping identify and fill gaps in current genomics databases. So much of the data we have today is based on samples from people of European ancestry, but by working with populations that are currently underrepresented in the genomic literature, we aim to create a more inclusive medical system.
