Border and his colleagues are not the first to raise the possibility of spurious genetic correlations. When designing studies, geneticists can control for the effects of factors like parental traits and childhood environment by comparing people who have those things in common—that is, siblings. Earlier this year, statistical geneticist Laurence Howe and a team of researchers did just that. When Howe compared siblings with each other, he observed no genetic correlation between BMI and years of education. Somehow, it was parents, and not genes themselves, that had made weight and education seem genetically connected.
But Howe’s study didn’t explain exactly how parents played a role. There were some promising possibilities. Parents don’t just pass down genes to their kids—they also pass down their socioeconomic status, which has consequences for both schooling and diet. And, of course, parents typically choose whom they reproduce with. Loic Yengo, group leader of the Statistical Genomics Laboratory at the University of Queensland, says that geneticists had realized that cross-trait assortative mating could—in theory—inflate genetic correlations. But no one had yet produced concrete evidence that it did.
Border and his colleagues found that evidence. Studying cross-trait assortative mating in detail requires knowing how much it actually happens in the real world. It seems reasonable that depressed people might end up with anxious people due to their shared experience of living with a mental illness, or that educated people would tend to marry people who got high scores on IQ tests, but Border needed to put numbers on those trends. The team was able to find the information they needed in the UK Biobank, an enormous dataset that comprises genetic, medical, and demographic data about hundreds of thousands of UK residents. They found that the more often people who had a particular pair of traits tended to couple up, the more those traits seemed to be genetically correlated. It was reasonable to suspect, then, that assortative mating was in fact making some genetic correlations appear stronger than they would otherwise be.
Still, this observation didn’t prove that assortative mating could create the illusion of a genetic link where none existed. So Border and his team turned to a computational approach: Following the marital trends they had observed in the real world Biobank data, they simulated a population of people who paired off into couples. These imaginary couples reproduced, and their children found mates, and their children’s children—and so on. The scientists tracked the genes and traits of all these simulated individuals, and, using that information, they were able to calculate genetic correlations across each generation. What they found confirmed their suspicions—even if two traits were totally genetically unrelated in the first generation, if people who had those traits tended to mate with each other, the genes eventually started to seem correlated. Based on the simulations, they estimated that assortative mating alone could explain as much as half of the genetic correlation between BMI and education.
But assortative mating didn’t go as far toward explaining some of the other apparent correlations they simulated. It appears to play a smaller role in the genetic correlations between some pairs of psychiatric conditions, like bipolar disorder and schizophrenia, or major depression and anxiety. Because each pair of conditions shares so many genetic similarities, some scientists have wondered whether they should even be considered separate conditions at all. Even taking assortative mating into account, that argument would still appear to hold water.
