After analyzing two giant databases of traits in pairs, the researchers found that the tendency of people to mate with others possessing related traits (often known as assortative mating throughout traits) correlates intently with estimates of genetic relatedness and certain performs an vital position in these estimates.
In line with the researchers, mating patterns might be able to clarify lots of the relationships between traits that have been beforehand considered organic.
New examine led College of California, Los Angeles signifies that present strategies for evaluating genetic associations between traits typically ignore the affect of mating patterns, resulting in overestimations of the power of genetic affiliation between traits and illnesses.
Scientists have used highly effective genome-sequencing know-how to attempt to uncover genetic hyperlinks between traits and illness danger in recent times, with the hope that this data will result in new illness therapies. Nevertheless, the examine performed by[{” attribute=””>UCLA and published in the journal Science warns against relying too heavily on genetic correlation estimates, as these estimates may be distorted by non-biological factors that have not been fully taken into account.
Genetic correlation estimates typically assume that mating is random. But in the real world, partners tend to pair up because of many shared interests and social structures. As a result, some genetic correlations in previous work that have been attributed to shared biology may instead represent incorrect statistical assumptions. For example, previous estimates of genetic overlap between body mass index (BMI) and educational attainment are likely to reflect this type of population structure, induced by “cross-trait assortative mating,” or how individuals of one trait tend to partner with individuals of another trait.
The study authors said genetic correlation estimates deserve more scrutiny since these estimates have been used to predict disease risk, glean for clues for potential therapies, inform diagnostic practices, and shape arguments about human behavior and societal issues. The authors said some in the scientific community have placed too much emphasis on genetic correlation estimates based on the idea that studying genes, because they are unalterable, can overcome confounding factors.
“If you just look at two traits that are elevated in a group of people, you can’t conclude that they’re there for the same reason,” said lead author Richard Border, a postdoctoral researcher in statistical genetics at UCLA. “But there’s been a kind of assumption that if you can track this back to genes, then you would have the causal story.”
Based on their analysis of two large databases of spousal traits, researchers found that cross-trait assortative mating is strongly associated with genetic correlation estimates and plausibly accounts for a “substantial” portion of genetic correlation estimates.
“Cross-trait assortative mating has affected all of our genomes and caused interesting correlations between
“But even when there is a real signal there, we’re still suggesting that we’re overestimating the extent of that sharing,” Border said.
Reference: “Cross-trait assortative mating is widespread and inflates genetic correlation estimates” by Richard Border, Georgios Athanasiadis, Alfonso Buil, Andrew J. Schork, Na Cai, Alexander I. Young, Thomas Werge, Jonathan Flint, Kenneth S. Kendler, Sriram Sankararaman, Andy W. Dahl and Noah A. Zaitlen, 17 November 2022, Science.
DOI: 10.1126/science.abo2059
The study was funded by the National Institutes of Health, the Chan Zuckerberg Initiative, the National Science Foundation, Open Philanthropy, and the Wellcome Trust.