Pardis’s Mission

As a graduate student, Pardis stumbled into the emerging field of computational genetics—the use of computers to help understand DNA sequences. She developed an algorithm that sifts through databases of human genetic information looking for traces of an elusive target: ongoing human evolution. To the general public, the idea that humans are still evolving can be surprising, but among evolutionary biologists it’s taken for granted. (One of the classic examples of recent human evolution is lactose tolerance—the ability to digest milk into adulthood—a trait that didn’t start spreading through the human population until we domesticated milk-producing animals.)

Pardis’s algorithm uses statistical techniques to hunt down patterns of gene migration that match what you would expect from selective pressure—for example, a mutation that popped up recently in human development but has since spread quickly among a population. The algorithm, in other words, searches blindly, turning up “candidate” genes that look like they’re the result of natural selection, but leaving it up to the researcher to figure out why natural selection deemed the gene useful.

Pardis uses the algorithm to search for recently evolved genes that provide disease resistance. Her logic is that if she can find these genes and understand how they work, biomedical researchers might be able to mimic their benefit in a treatment. It makes sense, of course, that disease-resistance genes would be among the candidates turned up by Pardis’s algorithm, as they provide a classic example of natural selection in action. If a deadly virus has been killing off humans in a population for a long time, biologists would say that this population is under “selective pressure.” If a lucky few members of the group then happen to evolve a resistance to the disease, this pressure ensures that the new gene will spread quickly (people with the new gene die less frequently than those without it). This rapid spread of a new gene is exactly the type of signature Pardis’s algorithm has been tuned to detect.

Pardis’s first big discovery was a gene that provides resistance to Lhassa fever, one of the oldest and most deadly diseases of the African continent, responsible for tens of thousands of deaths each year. (“People don’t just die with this disease,” she emphasized, “they die extreme deaths.”) She has since added malaria and the bubonic plague to the list of “ancient scourges” that she’s tackling with her computational strategy.

Pardis’s career is driven by a clear mission: to use new technology to fight old diseases. This research is clearly important—an observation emphasized by the fact that she’s received seven-figure grants for her work from both the Bill and Melinda Gates Foundation and the NIH. Later in this book, we’ll dive into the details of how she found this focus, but what’s important to note now is that her mission provides her a sense of purpose and energy, traits that have helped her avoid becoming a cynical academic and instead embrace her work with enthusiasm. Her mission is the foundation on which she builds love for what she does, and therefore it’s a career strategy we need to better understand.