
99 independent genetic loci influencing IQ/brain health/structure (n=280360) - gwern
http://www.biorxiv.org/content/early/2017/08/17/176511
======
zsmj
"Genetic association results predicted up to 4% of general cognitive function
variance in independent samples"

gwern, do you find that the effect predicted is too small? If these genes are
"highly expressed", I would expect the predicted variance to be greater.
Forgive my ignorance but this seems to point to the fact that other factors
vastly outweigh these SMPs.

~~~
gwern
'Highly expressed' here simply means that the variants in question tend to be
located in/affecting genes that are more active in CNS stuff, it doesn't refer
to the variance explained. You could identify a gene which is active only in
cells in a particular organ yet variants inside that gene might affect little
in the way of differences from person to person. This is useful for giving
mechanistic hints as to how the variants are having any causal effect; it's
also a useful sanity check, as if the IQ GWASes were turning up SNP hits
mostly in non-nervous-system expressed genes, it would be highly suspicious.

That said, one of the more counterintuitive aspects of GWAS is that it is
possible to identify many variants which affect intelligence while explaining
trivial amounts of variance - this is the central limit theorem in action on
the thousands of variants, because on net in normal people most variants just
cancel out and the genetic contribution to intelligence is relatively few
variants (most people differ by only 10 or 15 IQ points, so even if most of
individual differences are due to different sets of variants, and we know from
GWASes that single variants typically explain something like 0.10 points...),
you have to identify with great precision the effect of a great many variants
before you start being able to predict anything in normal people (This is
weird and counterintuitive and I don't yet have any good metaphors or examples
which can make it immediately understandable.)

Finally, on the gripping hand, 4% _is_ weirdly small because the same people
with a smaller sample (albeit boosted using MTAG/genetic correlations) were
able to produce a PGS explaining almost double the variance, 7%, in "A
combined analysis of genetically correlated traits identifies 107 loci
associated with intelligence"
[http://www.biorxiv.org/content/early/2017/07/07/160291.1](http://www.biorxiv.org/content/early/2017/07/07/160291.1)
, Hill et al 2017, and just yesterday "Large-Scale [n=107k] cognitive GWAS
Meta-analysis Reveals Tissue-Specific Neural Expression and Potential
Nootropic Drug Targets", Lam et al 2017
[http://www.biorxiv.org/content/early/2017/08/16/176842](http://www.biorxiv.org/content/early/2017/08/16/176842)
turned in the same 4% PGS despite different analysis & sample size, so I am
suspicious that the validation sample being used is misleading in some way
such as using lower-quality IQ measurements. (One of the problems in using
independent validation samples rather than something like cross-validation.)

