Current methods of assessing genetic relationships between traits are flawed

After studying two large databases on mate traits, the researchers found that an individual's propensity to mate with someone with similar traits (known as cross-trait selection mating) was strongly correlated with genetic correlation estimates and may play an important role
in these estimates.

According to the researchers, mating patterns may be able to explain many of the relationships
previously thought to be between biological traits.

A new study led by the University of California, Los Angeles shows that current methods of assessing genetic links between traits often ignore the effects of mating patterns, leading to inflated estimates
of the strength of genetic links between traits and diseases.

In recent years, scientists have been using powerful genome sequencing technology to try to uncover genetic links between traits and disease risk, hoping that this knowledge will lead to new treatments
for disease.
However, a study conducted by the University of California, Los Angeles (UCLA), published in the journal Science, cautions against relying too heavily on genetic correlation estimates, as these estimates can be skewed
by abiotic factors that are not adequately taken into account.

Genetic correlation estimates generally assume that mating is random
.
But in the real world, partners tend to form a couple
due to many common interests and social structures.
Thus, in previous studies, some genetic correlations attributed to shared biology may 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 demographic structure, caused by "cross-trait homotyping," or the tendency of individuals with one trait to mate with individuals with another trait
.

The study's authors say genetic correlation estimates deserve more scrutiny because they are already being used to predict disease risk, gather clues to potential treatments, inform diagnostic practice, and shape debates
about human behavior and social issues.
Some in the scientific community place too much emphasis on gene correlation estimation, the authors say, arguing that studying genes can overcome confounding factors because genes are immutable
.

Lead author Richard Border, a postdoctoral researcher in statistical genetics at UCLA, said: "If you just look at two traits in a group of people who are promoted, you can't conclude that they exist for the same reason
.
But there's an assumption that if you can trace genes, then you have cause and effect
.
”

Based on their analysis of two large databases of mate characteristics, the researchers found that cross-trait selection mating was closely related to genetic correlation estimates and reasonably explained the "considerable" portion
of genetic correlation estimates.

Study co-author Noah Zaitlen, a professor of computational medicine and neurology at UCLA Health Center, said: "Selective mating across traits affects all of our genomes and creates interesting correlations
across the genome between the DNA you inherit from your mother and the DNA you inherit from your father.
"

The researchers also examined estimates of genetic correlation of psychiatric disorders, which has sparked debate in psychiatric circles because they seem to show genetic relationships between disorders that seem to have little similarity, such as attention deficit hyperactivity disorder and schizophrenia
.
The researchers found that the genetic correlation of many uncorrelated traits appears to be attributable to cross-trait selection mating and imperfect diagnostic practices
.
On the other hand, their analysis found stronger links between certain traits, such as anxiety disorders and major depressive disorder, suggesting that at least some common biological traits
do exist.

"But even with real signals, we still think we're overestimating the extent of this sharing," Border said
.

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