HomeScienceGeneticsGenetic links between traits often exaggerated?

Genetic links between traits often exaggerated?

Many estimates of how strongly traits and diseases share genetic signals may be too high, according to a new UCLA-led study indicating that current methods for assessing genetic relationships between traits do not account for mating patterns.

Through the use of powerful genome sequencing technology, scientists have spent the last few years trying to understand the genetic associations between traits and disease risk, hoping that discoveries of shared genetics could point to clues for tackling disease. However, UCLA researchers said their new study, published in Science, cautions against relying too heavily on estimates of genetic correlations. They say such estimates are more confounded by non-biological factors than previously believed.

Genetic correlation estimates typically assume that mating is random. But in the real world, partners tend to work together because of the many shared interests and social structures. As a result, some genetic correlations in previous work 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 likely reflect this type of population structure, caused by “cross-trait assortative mating,” or how individuals with one trait tend to interact with individuals of another trait .

The study authors said genetic correlation estimates deserve more attention, as these estimates have been used to predict disease risks, gather evidence for potential therapies, inform diagnostic practices, and shape arguments about human behavior and societal issues. The authors said that some in the scientific community have placed too much emphasis on genetic correlation estimates based on the idea that studying genes, because they are immutable, can overcome confounding factors.

Must Read
Death in CRISPR Gene Therapy Study Leads to Search for Answers

“If you just look at two traits that are elevated in a group of people, you can’t conclude that they are there for the same reason,” said lead author Richard Border, a postdoctoral researcher in statistical genetics at UCLA. “But there’s been this sort of assumption that if you can trace this back to genes, you’d have the causal story.”

Based on their analysis of two large marriage trait databases, researchers found that cross-trait assortative mating is strongly associated with genetic correlation estimates and likely accounts for a “substantial” portion of genetic correlation estimates.

“Cross-trait assortative mating has influenced all of our genomes, causing interesting correlations between DNA you inherit from your mother and DNA you inherit from your father across the genome,” said study co-author Noah Zaitlen, a professor of computational medicine and neurology at UCLA Health.

The researchers also examined estimates of genetic correlations of psychiatric disorders, which have sparked debate in the psychiatric community because they appear to show genetic relationships between disorders that appear to bear little resemblance, such as attention deficit hyperactivity disorder and schizophrenia. The researchers found that genetic correlations for a number of unrelated traits can plausibly be attributed to cross-trait assortative mating and imperfect diagnostic practices. On the other hand, their analysis found stronger associations for some pairs of traits, such as anxiety disorders and major depression, suggesting there really is at least some shared biology.

“But even if there’s a real signal, we’re still suggesting that we’re overestimating the magnitude of that sharing,” Border said.

Reference: Grens R, Athanasiadis G, Buil A, et al. Cross-trait assortative mating is widespread and increases genetic correlation estimates. Science. 2022;378(6621):754-761. doi: 10.1126/science.abo2059.

Must Read
Dennis Lo receives prestigious Lasker Award 2022

This article has been republished from the following materials. Note: Material may be edited for length and content. For more information, please contact the source mentioned.



Please enter your comment!
Please enter your name here

Most Popular

Recent Comments