Genes can predict sexual orientation in men

In a first, scientists have developed a method that can almost accurately reveal the sexual orientation of men just by looking at some specific genes.

The team is now ready with a predictive model that can help people understand their sexual orientation better.

In trials, an algorithm using genetic information from just nine regions of the human genome predicted the sexual orientation of males with up to 70 percent accuracy.

"To our knowledge, this is the first example of a predictive model for sexual orientation based on molecular markers," said Tuck C Ngun, postdoctoral researcher at University of California-Los Angeles.

Beyond the genetic information contained in DNA, the researchers examined patterns of DNA methylation - a molecular modification to DNA that affects when and how strongly a gene is expressed - across the genome in pairs of identical male twins.

While identical twins have exactly the same genetic sequence, environmental factors lead to differences in how their DNA is methylated.

In all, the study involved 37 pairs of twins in which one twin was homosexual and the other was heterosexual, and 10 pairs in which both twins were homosexual.

"A challenge was that because we studied twins, their DNA methylation patterns were highly correlated," Dr Ngun explained.

Even after some initial analysis, the researchers were left with over 400,000 data points to sort through.

To sort through this data set, Dr. Ngun and his colleagues devised a machine learning algorithm called FuzzyForest.

They found that methylation patterns in nine small regions, scattered across the genome, could be used to predict study participants' sexual orientation with 70 percent accuracy.

Previous studies had identified broader regions of chromosomes that were involved in sexual orientation.

"We were able to define these areas down to the base pair level with our approach," Dr Ngun added.

Sexual attraction is such a fundamental part of life but it is not something we know a lot about at the genetic and molecular level, the authors noted.

They are currently testing the algorithm's accuracy in a more general population of men.

The findings were shared at the American Society of Human Genetics (ASHG) 2015 annual meeting in Baltimore this week.