People don’t mate randomly – but the flawed assumption that they do is an essential part of [genome wide association studies], Border & Zaitlen, 2022

Virtually all the statistical methods researchers commonly use to assess genetic correlations assume that mating is random. That is, they assume that potential mating partners decide who they will have children with based on a roll of the dice. In reality, many factors likely influence who mates with whom. The simplest example of this is geography – people living in different parts of the world are less likely to end up together than people living nearby.

(…)

We found that taking into consideration the similarities across mates could strongly predict which traits would be considered genetically linked. In other words, just based on how many characteristics a pair of mates shared, we could identify around 75% of the presumed genetic links between these traits – all without sampling any DNA.

Study: https://www.science.org/doi/10.1126/science.abo2059

Article in the Conversation: https://theconversation.com/people-...s-linking-genes-to-diseases-and-traits-194793

@Simon M @Chris Ponting @Andy

 

Well, I'm not the expert on these things but I would assume that is one of the reasons why we are using the data from the UK Biobank as our control group, thereby controlling for geography as much as is possible.

 

From the article - not the paywalled study - this seems to be both competent and timely, a necessary caution about what GWAS can and can't do. But I don't think it changes the value of GWAS as a prospecting tool, especially with an illness(es) such as ME/CFS where there are so few clues as to where to look using other methodology.