Million-person genetic study finds gene patterns linked to how long people stay in school
The largest-ever genetic study on human cognition has found more than 1,000 links between people’s genes and how far they get in school.
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The work, which involved DNA from 1.1 million people and researchers drawn from 40 institutions, led to a scoring system that can roughly predict how educated someone is by examining that person’s DNA.
Those with the lowest genetic scores had only a 10 percent chance of having graduated from college. By contrast, those in the highest quintile of genetic promise did so 50 percent of the time.
It is no surprise that how far a person gets in school is partly determined by genes. Studies of identical twins raised apart, for example, show they are strikingly similar. Until recently, however, scientists did not have the tools to locate the genes that influence human behaviors.
What’s changed is that researchers can now study far larger groups of people. That allows them to zero in on minute differences in the genome that, acting together, help explain how tall a person is, or how likely to develop a common disease like diabetes—or even how smart.
“This paper will [be] a landmark in this new kind of social science,” says Eric Turkheimer, a psychologist at the University of Virginia, who was not involved in the study. “As a very successful application of new genetic technology, it is extraordinary.”
Specifically, the big haul of education-linked genes will allow scientists to “begin to ask questions about how individual genes contribute to biological pathways that eventually lead to brains and learning,” he says.
The new effort to link DNA to education, described today in Nature Genetics, is among the first to assess the genes of over one million people simultaneously. It employed more than 400,000 DNA profiles collected in Britain as part of the national UK Biobank project, and another 365,536 were provided by 23andMe, the San Francisco–area consumer gene testing company.
Some researchers say the discoveries will permit assessment of children’s learning potential from their DNA in the form of a genetic intelligence test, giving parents or school systems a way to identify those with extra promise or explain why others have trouble.
The authors of the current study strongly dispute that idea. In a FAQ document they distributed to journalists, they said their scoring system was merely a scientific tool. “Any practical response—individual or policy-level—to this or similar research would be extremely premature and unsupported by the science,” they wrote.
According to Daniel Benjamin, a behavioral economist at the University of Southern California who is one of the study’s lead authors, the predictions are still too unreliable to apply to individuals. The genetic variants he and his colleagues measured can explain only about 11 percent of the variability between people in educational attainment.
“Until the score is better and we understand the causal factors underlying it, I am pretty uncomfortable using it to predict individual outcomes,” Benjamin said. “There is a lot more work to be done before we even have a conversation about using it that way.”
Still, Benjamin acknowledged that DNA is now a better predictor of how long people stay in school than whether they grow up in a rich or poor household, and almost as good a predictor as the education level of their parents.
Researchers say this new type of genetic assessment, termed a polygenic risk score, can also give insight into a person's chance of developing heart disease, mental illness, or other conditions.
Exactly how genes create a tendency toward more or less educational attainment remains fundamentally unclear. It could result from the action of other traits, such as conscientiousness, intelligence, or even body mass. The effect of genes is also hugely contingent on social context. In a society without formal schooling, for example, people’s DNA would say nothing about what level of education they finish.
“These are not genes that have the same effect everywhere,” says Turkheimer. “Instead, they influence outcomes in subtle, contextually sensitive, and hard to trace ways, with effects that can only be detected in enormous samples.”
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