Genetically, human beings—each and every one of us—are 99.9% identical. Considering our diversity and all the little things that makes us wonderfully different from one another, that might seem impossible. But consider this: that other tenth of a percent of your genome accounts for almost 6.5 million DNA bases! What’s more, DNA variants can be combined in myriad ways, adding even more diversity. For geneticists, these variants can be an invaluable resource for exploring and understanding our health.
A number of fields study these variations and their implications. The field of genomics studies individual genomes and compares them against a “standard” reference sequence to gain insights. Population genomics is a very similar field, but goes further than looking at a single individual’s DNA—instead, it looks at genetic variation across the genomes of people within a designated group. Researchers study the frequencies of DNA variations within these groups, along with how those frequencies have changed over time and geographic location. A big benefit of this approach is that it helps scientists recognize trends in a population, which can then be used to identify potential disease-causing variants.
The importance of ancestry
These research groups are best described based on ancestry—not race or ethnicity, as some might expect. There’s a very good reason for this: people sometimes self-identify with a race or ethnicity based on the geographic location where their recent ancestors came from. For example, someone whose grandfather was from China will assume they’re at least part Asian. However, oral and written records of our family trees only go back so far—and are only so accurate. Someone who self-identifies as Asian may actually have ancestral roots that extend throughout eastern Europe and into Africa.
One reason why ancestral histories are complicated and gene pools are so diverse is that as human populations migrated to new locations, they mixed with groups they’d been isolated from for thousands of years. This mixing resulted in new groups. For instance, modern Europeans can trace most of their ancestry to at least two divergent groups that mixed when early farmers settled a territory formerly inhabited only by hunter-gatherers. More recently, genetic studies have found that the ancestry of urban Mexicans is more or less evenly split between European and Native American, with a trace of African. This is a result of Spanish colonization and mixing with resident populations that had been living in that territory for millennia.
On the other hand, there are populations that have stayed fairly isolated, like Icelanders. The Icelandic gene pool has less genetic variation, which reduces the “background noise” when trying to identify variants that affect one’s health. This, coupled with Iceland’s extensive genealogical and medical records, makes them an ideal source for a lot of medical DNA research—and discoveries.
Impacts on health and medicine
Variations in traits among human populations represent genetic differences that can be inherited from generation to generation. Sometimes this can take the form of something like dietary intolerance, or susceptibility to certain diseases. Thanks to population genetics, we can tune genetic screening practices for certain groups of people. A well-known example of this is testing for sickle cell anemia in people whose parents both have African ancestry. Likewise, individuals of European descent are likely to get tested as carriers for cystic fibrosis. Ashkenazi Jews, on the other hand, are more likely to be screened for the very rare Tay-Sachs disease prior to pregnancy.
Population genetics also helps find what are called pharmacogenetic variants—genetic variations that cause some groups to respond differently to certain medications. We’ve learned, for example, that one set of genetic variants influences the recommended dose of Warfarin (a drug that helps prevent vein thrombosis) in people with European ancestry, while a different set of genetic variants informs the dosing for people of African descent.
This is not to say that DNA has full reign over the general health of a population. Living conditions, environmental hazards, access to proper medical care, and nutrition quality often play more important roles. DNA research and discovery is complex, which is why having larger datasets (and thus higher-quality data) is so important.
Why underrepresented groups should participate
While populations are studied based on ancestry rather than simply race or ethnicity, it’s important to recognize that certain racial groups have been underrepresented in genetic testing. Until recently, the majority of research has been conducted on European genomes, and this can unfortunately, lead to inconclusive testing results for underrepresented groups. The best way to improve testing outcomes for non-European groups is to expand the diversity of testing sets. (The goal of the 1000 Genome Project was to do just this: It was the first project to sequence the genomes of a diverse group of people—2,504 people from 26 populations—in order to help alleviate this bias.)
It’s also important to be aware of preconceptions when it comes to health matters. Relying on race or ethnicity when deciding who gets tested for what, or for determining courses of treatment, could lead to oversights. Cystic fibrosis, for example, is considered a “white” disease—but that doesn’t mean someone of another race can’t develop it.
The benefits of patterns
Population genetics gives us an opportunity to step back and observe patterns of genetic change over time. By comparing populations to each other (and to themselves), we can begin to see how outside factors might spark the evolution of a trait. It also allows us to map variants associated with traits that vary across populations, giving us insights into health-related differences among groups, like why some groups are more susceptible to certain diseases.
Overall, population genetics is another way of looking at DNA that can yield insights with the potential to benefit everyone. By comparing groups of data—rather than individual sequences—to a single standard, we open up a new avenue for making health discoveries. And just as importantly, we learn about ourselves by learning how our genetic makeup came to be.
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