I would interpret these findings very differently. What the authors do is analyse GWAS data in a very unusual way – they are not interested in finding specific SNPs affecting the trait, they simply use the SNPs to measure genetic relatedness between individuals. (Well, they were interested in findings specific SNPs but once they didn’t find any significant ones they turned to this other kind of analysis). Razib, you say that the people in the study are unrelated but they are not – they are all from the same population and are distantly related. The study uses SNPs across the genome to measure this relatedness and then shows it correlates with phenotypic similarity – i.e., the trait is heritable. We knew that already.

What they claim is that you can break down this effect by chromosome or by subregion. When they use the SNPs along longer chromosomes they seem to get a bigger effect – “explaining more of the phenotypic variance”. The inference is that thousands of SNPs, scattered across the whole genome, contribute to the trait or, more specifically to variance in the trait across the population (the implication is that they contribute to the value of the trait in individuals).
There is an alternative explanation for this effect, however, which is that using more SNPs simply gives a better estimate of genetic relatedness. So, the SNPs on chromosomes 1 (the longest) give a better estimate than those on chromosome 21 (the shortest) – they index relatedness with more precision. As a result, they correlate better with phenotypic similarity – this looks like you have “explained more of the variance”. In fact, getting such a signal from SNPs on chromosome 1 does not mean that any of the causal variants are actually on chromosome 1. Nor does the fact that such signals can be derived from anywhere in the genome mean that there are thousands of variants across the genome affecting the trait.
In fact, the authors can conclude very little from this study beyond a replication of the known fact that IQ is heritable.

They can say nothing about how many variants are involved across the population or how many affect the trait in each individual. Note that those could be very very different from each other – you could have hundreds or thousands of genes affecting a trait across the population, but only one, two or a handful of variants affecting the phenotype in any individual. Nor can they say whether the causal variants are common or rare. One could expect different combinations of small numbers of different rare variants to be determining phenotype in different individuals. In fact, I would say that is exactly what one should expect. Not the picture they try to sell in this paper, which is that the phenotype in any individual is determined by the combination of thousands of common variants.

I don’t know where I dug out that 1/2 in my note above: senescence perhaps.

Henry

Henry Harpending

http://www.nature.com/nature/journal/v476/n7358/full/476027a.html

Kevin.