People’s health and lifestyle are influenced by the genes of their partners, according to a study published last month (December 14) in Nature Human Behavior. Using data from more than 80,000 couples in the UK Biobank, researchers identified multiple correlations between individuals’ traits and their partners’ genomes, and concluded that around one-quarter of those associations were partly causal, with one person’s DNA having indirect effects on the other person’s health or behavior.
“I was really excited to see this paper,” says Emily McLean, an evolutionary biologist at Oxford College of Emory University in Georgia who was not involved in the work. “Intuitively, it seems like, of course our behaviors are influenced by the individuals around us, and likely by the genes that those individuals are carrying. So it was really great to see some empirical support for that intuitive idea.”
Unlike direct genetic effects, which reflect the influence of your own genes on your phenotype, indirect genetic effects are a form of environmental influence, driven by the genetic traits of people around you. In a simple hypothetical example, a person who is genetically predisposed to smoking might raise their partner’s risk of lung cancer via exposure to cigarette smoke or by encouraging them to smoke more.
Several studies have provided evidence of these indirect effects in nonhuman animal populations, and a couple of studies on specific traits in humans—including schoolchildren’s propensity to smoke and their educational attainment—have suggested that people, too, are affected by the genetic makeup of their peers. But it hasn’t been clear how widespread these effects are in human relationships, nor whether the associations themselves are causal rather than correlational.
In the current study, the University of Edinburgh’s Charley Xia, Albert Tenesa, and colleagues used data from 80,889 heterosexual couples of European ancestry whose genetic variation and health and lifestyle habits are recorded in the UK Biobank. The researchers selected 105 complex traits—those influenced by variation in multiple genes such as height, smoking status, and susceptibility to mood swings—and used a statistical model to look for broad associations between each individual’s traits and their partner’s DNA.
The team found that around 50 percent of these traits showed some correlation with the partner’s genetic makeup. Many of those correlations could have been due to assortative mating, Xia says. For instance, people may be more likely to choose partners with traits similar to their own, creating spurious relationships in the data. Height is a typical example of a trait likely to be correlated in couples due to assortative mating rather than any indirect genetic effects, he adds.
The researchers ran computer simulations of mix-and-match combinations of individuals in their dataset to see if they could distinguish between associations due to assortative mating and those due to true indirect genetic effects. They concluded that around 25 percent of the associations did indeed involve at least some causation—that is, one person’s genotype was having a detectable effect on another person’s phenotype.
These associations included several dietary traits, such as self-reported poultry and beef intake, time spent watching television, susceptibility to mood swings, and smoking habits, although the team did not explore specific traits or genes in detail. Height did not show evidence of a causal relationship using this analysis, Xia says, increasing the researcher’s confidence in their method.
While it’s hard to draw conclusions about individual traits from this kind of broad analysis, the team’s study represents a proof of concept that indirect genetic effects may be important in humans, says Daniel Belsky, an epidemiologist at Columbia University Mailman School of Public Health who was not involved in the work. He calls it a “creative application of a large and powerful database to address an important and open question in behavioral genetics.”
Belsky adds that while the results “seem broadly sensible,” there remain some questions for future studies regarding the extent to which indirect genetic effects can be distinguished from assortative mating. “The design that [the authors] use is quite strong in controlling for assortment on the trait under analysis,” he notes, but it’s less effective “for controlling for assortment on traits that are genetically correlated with the trait under analysis but which may not be measured.”
McLean says she’d be interested to learn more about the mechanisms behind the associations the team identified, and about which genes in one person are related to which trait in the other. She cautions that some of the UK Biobank data used in the study is self-reported, and so researchers would need to check that responses accurately reflect people’s traits. Determining the direction of genes’ effects on behavior—that is, whether a particular trait is positively or negatively associated with a genotype in the partner—could also be an interesting next step from an evolutionary perspective, McLean adds.
Xia notes that to properly understand the mechanisms responsible for the effects the team identified, the researchers would need to focus more closely on individual traits, and use data on genes and lifestyle from the same people spanning many years—a follow-up project that some of the team members are currently considering, he adds.
Such data on indirect genetic effects could one day have applications in public health, Belsky says. “It may be possible, as genomes become a routine part of a person’s medical record, to provide clinical guidance and risk management information to patients based on partner genotypes,” he says.
More immediately, the study is an important reminder of the complexity of genotype-phenotype relationships, Belsky adds. “Observations like this . . . illustrate ways in which a wide range of environments—in this case, another person you’ve chosen to share your life with—intercede between the genetic risk a person is born with and the health outcome that we’re interested in protecting them from. This is another argument against a deterministic interpretation of a person’s genetic background, when you think about the kind of life that they’re going to lead and the sort of health risks they’re going to have.”
C. Xia et al., “Evidence of horizontal indirect genetic effects in humans,” Nat Hum Behav, doi:10.1038/s41562-020-00991-9, 2020.
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