For precision medicine to live up to its name, a more comprehensive understanding of the human genome is required. Why is it that some of us are more genetically predisposed to certain diseases than others? What genetic factors of our ancestry play a role here? And what other factors govern our immune response to diseases?
“There are a lot of these genetic prediction algorithms out there, but the problem is they don’t perform well when they’re tested in people of different ancestries than the prediction was created from,” said Brenna Henn, associate professor of anthropology and associate director of human genomics at the UC Davis Genome Center.
Currently, such genetic prediction algorithms are typically designed based on populations with European ancestries, meaning those with non-European ancestries rarely benefit from them. To democratize the space, the Henn Lab is spearheading two projects funded by the National Institutes of Health for nearly $812,000.
How common are gene interactions?
In a project funded by the National Human Genome Research Institute for $431,300, the Henn Lab will examine how epistasis, or gene-by-gene interactions, impacts individual traits.
“We’re specifically looking at one factor that is very under-explored and that’s the idea that some of these mutations that are linked to phenotypes or disease, they could behave differently in different genetic ancestries,” Henn said. “In one genetic ancestry, they might increase the risk of heart disease or something, but when they’re in a different genetic ancestry, it no longer has that effect.”
To better understand how genetic associations might vary across ancestries, the Henn Lab is studying DNA methylation.
“Every cell in your body has the same genetic code, and DNA methylation is one aspect that controls what genes are turned on and off. It’s what causes, for example, a blood cell to be a blood cell, or a nerve cell to be a nerve cell,” said Gillian Meeks, a Ph.D. student in the Henn Lab. “It’s a chemical mark that sits on top of the DNA.”
DNA methylation also plays a role in disease risk and gene expression.
“There’s this potential for this little chemical 'hat' that gets read by other machinery in the cell to determine whether gene expression is occurring,” said Henn. “What we’re trying to measure is whether there are gene-gene interactions when two genes sit locally nearby each other on a chromosome.”
The team will study variation in DNA methylation using samples collected from 500 people in South Africa. Meeks’ analysis will be so detailed that she’ll be able to pinpoint which parts of a person’s chromosome stem from different ancestries. The goal is to test whether genetically-driven methylation changes differ depending on the genetic ancestry of the chromosome.
The extent of gene-by-gene interactions they uncover using methylation can inform disease-based genetic prediction.
The research could help expand the benefits of precision medicine to those of non-European descent.
Characterizing tuberculosis immune response
In a separate project, funded for $380,774 by the National Institute of Allergy and Infectious Diseases, the Henn Lab is laying the groundwork to advance care against the world’s top infectious killer: tuberculosis (TB).
“The preventative measure for TB is the Bacillus Calmette-Guérin (BCG) vaccine, which was created over 100 years ago,” said Oshiomah Oyageshio, a Ph.D. student in the Henn Lab. “There have been no approved updates since then.”
What’s more, the BCG vaccine doesn’t work well in adults, necessitating the development of a better vaccine. Doing that requires a molecular understanding of how TB progresses, which can then inform TB treatments and vaccines.
The Henn Lab will perform single-cell RNA sequencing on immune cells from individuals infected with TB through three stages of the disease: latent TB infection, recently progressed to active TB and post-TB treatment completion. The project’s dataset includes genetic information from 225 South African people, 125 have latent TB and 100 are TB cases sampled near the time of their diagnosis and longitudinally after they completed medical treatment.
Single-cell RNA sequencing allows scientists to analyze a cell’s transcriptome — the entire range of genes it can express. Oyageshio likened the process to reverse-engineering a smoothie. Single-cell RNA sequencing helps one discern the specific ingredients that went into the smoothie. For a cell, it can tell how genes shift and differ during various states of disease.
“Every disease involves a whole repertoire of different cells doing different things,” Oyageshio said. “We’re measuring gene expression per unique cell type and we’re also measuring protein expression. We’re combining these different modes of information to define these cell-type clusters really well.”
The research is a collaboration with Marlo Möller, of Stellenbosch University in South Africa and Sara Suliman, of University of California, San Francisco.
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