The linked paper says:
We fitted a linear mixed model
y = µ + g + e, whereyis the phenotype,mis the mean term,gis the aggregate additive genetic effect of all the SNPs and e is the residual effect.
If you have 3511 individuals and 549692 SNPs you won't find any nonlinear effects. 3511 observations of 549692 SNPs is already overfitted 3511 observations of 549692 * 549691 gene interactions is even more overfitted and I wouldn't expect that the four four principal components they calculate to find an existing needle in that haystack.
Apart from that it's worth noting that IQ is g fitted to a bell curve. You wouldn't expect a variable that you fit to a bell curve to behave fully linearly.
You wouldn't expect a variable that you fit to a bell curve to behave fully linearly.
I would not recommend making confident pronouncements which make it evident you have no clue what you are talking about.
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