More educated people typically weigh less, according to statistics. To come up with convincing answers may be a game played in a parlor, but that correlation by itself doesn't actually tell you much. The availability of healthier foods for persons with higher levels of education may be the cause. Perhaps this is because overweight people who are bullied are more prone to drop out of school. Alternatively, perhaps those who can afford both gym memberships and college tuition are the same folks.
A study published in Nature Genetics in 2015 raised an unexpected new hypothesis: Perhaps the reason education and weight are so closely correlated genetically is that they share some genetic antecedents. The study's authors looked for pairings of qualities that were associated with the same genes using huge databases of genetic information. They produced a statistic known as "genetic correlation" for each pair, which measures how close the entire set of genes connected to one feature is to that linked to another one. Body mass index (BMI) and years of education are two traits that stood out as having significant genetic correlations. Other pairs that were more obvious included type 2 diabetes and blood glucose levels and depression and anxiety. (Researchers have since attempted to explain the apparent genetic relationship between weight and education by proposing that individuals who are genetically predisposed to make better decisions and are likely to succeed in the classroom are more likely to adopt healthy lifestyles.)
Such genetic theories may seem implausible in comparison to more straightforward behavioral ones. The facts, however, appear to provide few other options. The primacy of genes is undeniable, after all. It makes sense to assume that traits like education and BMI have entwined biological underpinnings if the same genes are linked to both of those variables.
Currently, a new study published in Science disproves this notion. It implies that geneticists should also take into account a person's parents, who are a person's first set of genes. Two qualities may not actually share any genes even if they are statistically linked to the same genes: If individuals who have similar features frequently mate, the same pattern may also manifest. Cross-trait assortative mating is the term for this process.
People with extensive education, who are likely to belong to a higher social class, for instance, frequently look for partners who exhibit social status indicators like a low BMI, and vice versa. Consequently, both high education and low weight are associated with genes in their offspring. The two features will appear to share some genetic reasons if this occurs often in a population because the traits and genes will co-occur so frequently. The truth is that they will have come from various familial branches.
Richard Border, a postdoctoral scholar in neurology and computer science at the University of California, Los Angeles and the study's lead author, claims that genetic correlations have gained popularity because of what they appear to imply about the underlying biology of a set of features. However, cross-trait assortative mating refutes these conclusions. It is essentially a method of defying that logic, according to Border.
The idea of erroneous genetic relationships has been raised by others besides Border and his associates. Geneticists can account for the effects of variables like parental characteristics and childhood environment when planning studies by comparing siblings to individuals who share those characteristics. This is exactly what statistical geneticist Laurence Howe and his team of researchers did earlier this year. Howe found no genetic relationship between BMI and years of education among siblings who were compared to each other. The apparent genetic link between weight and education was somehow caused by parents rather than the genes themselves.
However, Howe's study left open the question of how exactly parents contributed. There were some exciting opportunities. Not only do parents pass down genes to their children, but they also pass down their socioeconomic standing, which has an impact on both diet and education. Of course, parents usually choose and choose who they have children with. Geneticists were aware that cross-trait assortative mating may, in theory, increase genetic connections, according to Loic Yengo, group leader of the Statistical Genomics Laboratory at the University of Queensland. But no one has yet shown proof in the form of hard data that it did.
That proof was located by Border and his colleagues. Knowing how frequently cross-trait assortative mating occurs in nature is essential to understanding it in depth. Although it appears logical that educated people would choose to marry persons with high IQ scores or that sad people could end up with anxious people owing to their common experience of living with a mental illness, Border needed to provide data to support these trends. The team was successful in locating the data they required in the UK Biobank, a sizable dataset that contains genetic, medical, and demographic information about hundreds of thousands of UK citizens. They discovered that a pair of traits appeared to be more closely associated genetically the more frequently persons with that pair of traits tended to marry up. So it made sense to hypothesize that assortative mating would be causing some genetic relationships to appear greater than they actually are.
This observation did not, however, demonstrate that assortative mating could feign a genetic connection where none actually existed. So Border and his team decided to take a computational approach. They simulated a population of individuals who paired off into couples while also taking into account the marital trends they had noticed in the real-world Biobank data. These fictitious couples gave birth to children, who in turn found partners and had offspring, and so on. These simulated people' genes and traits were monitored by the researchers, who used this data to determine genetic correlations between each generation. What they discovered supported their suspicions: even if two features were entirely genetically independent in the first generation, if individuals who possessed those traits tended to mate with one another, the genes gradually started to seem associated. They predicted that the simulations could account for up to half of the genetic link between BMI and education.
However, assortative mating fell short of providing a comprehensive explanation for several of the other apparent connections they simulated. It seems to have less of an impact on the genetic relationships between other psychiatric disease pairs, such as bipolar disorder and schizophrenia or major depression and anxiety. Some researchers have questioned whether each combination of illnesses really has to be treated as independent ones since they are so genetically related to one another. That seems to stay true even when assortative mating is taken into account.
According to Verneri Anttila, a genetics researcher at the University of Helsinki, this is especially encouraging news given the situation of psychiatry today. According to him, genetic analysis has been a rare source of hope in the last ten years. While certain techniques to diagnosing and treating mental illness appear to have reached a dead end, genetic research has continued to provide light on the condition and may one day help develop novel therapies.
In spite of the evidence he and Border have presented, senior author of the research and UCLA professor of neurology Noah Zaitlen doesn't anticipate that the genetics community will quickly alter its technique. And achieving it was never his aim. He asserts that performing too many tests and trying too many different things can actually halt progress. He anticipates that when interpreting the results of genetic correlation, scientists would now have to take the potential impact of assortative mating carefully.
According to Border, this research may have its most significant effects away from the lab. Some individuals are attempting to apply genetic technologies to the actual world as they develop and scientists become better at predicting how people will appear and behave simply by looking at their genomes. If you spit into a plastic tube and send it to their lab, for instance, 23andMe will use your genes to estimate your risk of developing type 2 diabetes. Furthermore, some scientists have proposed that schools employ genetic analysis to more effectively allocate resources to their pupils because it is possible to predict a person's academic performance simply by looking at their DNA.
However, it's difficult to state for sure that genes can tell you something about a child's inherent capacity to succeed in school if social factors like cross-assortative mating can significantly impact the outcomes of genetic studies. According to our findings, this is a rather bad idea, Border claims.
He is presently looking into how familial traits other than cross-trait assortative mating, such as the transmission of social class and economic status, might provide the appearance of genetic links. He is now convinced that genetic prediction techniques are not suitable for widespread use in fields like education thanks to his research and his work on assortative mating. Before we begin with this, he claims, "we really need to fully grasp what we're actually measuring, especially with behavioral features."
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