
Gene discovery from a genome-wide association study of educational attainment - gwern
https://www.dropbox.com/s/2x277c71kuszwwt/2018-lee.pdf?dl=0
======
pwdisswordfish2
> “If you did a study like ours 100 years ago, the strongest genetic predictor
> of education would be how many X chromosomes you had, because society was
> set up in a way that it was much harder for women to get educated than men,”
> says Benjamin. Likewise, many of the genes that are associated with
> education today are likely important “because of how today’s educational
> system is set up. It requires people to sit at desks for hours, and listen
> to instructions from a teacher. People who get restless, or are less
> obedient to authority, will fare less well in that environment.”

I think the above snip (ha) from
[https://www.theatlantic.com/science/archive/2018/07/staying-...](https://www.theatlantic.com/science/archive/2018/07/staying-
in-school-genetics/565832/) is useful in interpreting the results.

~~~
wycs
I would much prefer direct IQ correlates rather than using education as a
proxy for something better measured with IQ tests.

~~~
projectramo
What is “better measured” with IQ tests?

~~~
laretluval
Intelligence.

~~~
projectramo
I see so much work before me. Just google it:

[https://futurism.com/intelligence-changing-what-you-think-
yo...](https://futurism.com/intelligence-changing-what-you-think-you-know-
part-one/)

~~~
frgtpsswrdlame
Do you have more good info on the subject?

------
gwern
Media:
[https://www.theatlantic.com/science/archive/2018/07/staying-...](https://www.theatlantic.com/science/archive/2018/07/staying-
in-school-genetics/565832/)

FAQ: [https://www.thessgac.org/faqs](https://www.thessgac.org/faqs)

------
xenadu02
From the FAQ:

> The current study further confirmed the finding from our earlier work that
> the effects of individual genetic variants on educational attainment are
> extremely small. The average effect size across the 1,271 genetic variants
> was just 1.8 weeks of schooling per allele; even the SNPs with the strongest
> associations only predicted around 3 weeks of additional schooling per
> allele. Taken together, these 1,271 SNPs accounted for just 3.9% of the
> variation across individuals in years of education completed. ​ > Here is
> another way to think about this result. Imagine that we used the results for
> these 1,271 genetic variants (not the ~1 million SNPs across entire genome
> we discuss in FAQ 2.3) to predict the educational attainment for a new group
> of people (separate from our discovery sample). We could then compare each
> individual’s predicted educational attainment to their actual educational
> attainment. If we did so, our results suggest that we would find that the
> predictions and actual outcomes correlate only very modestly (at about r =
> 0.20). That, in turn, means that if someone were predicted to complete an
> above average number of years of schooling (i.e., to be in the top half of
> educational attainment), that person would have about a 58% chance of
> actually being in the top half of educational attainment. Fifty-eight
> percent is better than chance (i.e., 50%), suggesting that a prediction
> based on these 1,271 SNPs has more power to predict educational attainment
> than a coin flip—but only a bit more power. By contrast, a prediction based
> on a polygenic score that combines ~1 million SNPs that we studied (see FAQs
> 1.5 & 2.3) has more predictive power: r = 0.33, corresponding to 11% of the
> variation across individuals. ​ > The contrast between the 3.9% of the
> variation predicted by the 1,271 SNPs and the 20% known to be explained by
> common SNPs (see FAQ 1.7) implies that there are many other SNPs that have
> not yet been identified. Even larger sample sizes will be needed to identify
> them.

They only included people of European ancestry to eliminate sources of noise
and cofounding factors. The effect size is very small, yet it does exist.

This seems to prove that intelligence influenced by genetics but is affected
by many thousands of genetic variations. There is no "smart" gene, just lots
and lots of randomness.

~~~
fwip
>This seems to prove that intelligence influenced by genetics

Only if the educational attainment difference predicted by these genes is
because of "intelligence." It could just as easily have to do with "stick-
with-it-ness" or "I-have-parents-that-insist-I-go-to-college" or "I-do-what-
is-expected-of-me."

------
haberman
I absolutely love that this study was accompanied by a FAQ
([https://www.thessgac.org/faqs](https://www.thessgac.org/faqs)).

My interpretation of this FAQ is that it provides a great deal of context that
would be apparent to people in the field (and therefore not included in the
paper itself) but is critical background for anyone else who is trying to make
sense of it.

It therefore provides a bridge between the highly technical paper itself and
journalism which too often misunderstands the true meaning of research
results.

I think this is so valuable. I hope that this kind of thing will catch on for
more research that attracts public interest.

~~~
21
I think the FAQ has a strong self-defence purpose. See the last question
covered, which is probably the first one people care about:

> 3.7. Could this kind of research lead to discrimination against, or
> stigmatization of, people with the relevant genetic variants? If so, why
> conduct this research?

------
peregrine
Has anyone made a tool to run your own 23andme genome data through this and
get a score yet?

~~~
jjtheblunt
check out promethease.com

------
rfinney
The 207 page Supplementary Material is here: [https://static-
content.springer.com/esm/art%3A10.1038%2Fs415...](https://static-
content.springer.com/esm/art%3A10.1038%2Fs41588-018-0147-3/MediaObjects/41588_2018_147_MOESM1_ESM.pdf)
(probably pay walled).

Interesting discussion of genes and pathways involved around page 84.
"Results: Causal Genes and Enriched Gene Sets"

I'll just type in the pathways. ( Supplementary Figure 22.) "Brain Specific
Expression of Significantly Enriched Gene Sets across Development. (page
196)": Chromatic modification, protein binding transcription factor activity,
npBAF complex, Central nervous system neuron differentiation, forebrain
development, partial posttnatal lethality, abnormal cerebral cortext
morphology, endometrial cancer , GAB1 signalosome, regulation of nervous
system development, telencephaol cell migration, protein tyrosine kinase
activity , neuron recognition, axon guidance, small cerebellum protein
phosphatase regulator activity, signaling by eGFR, dendrite morphogenesis,
signaling by NGF, regulation of neuron projection development, behavioral fear
response, DAG and IP signaling, associative learning , voltage-gate calcium
channel activity , ataxia, extracellular-glutamte-gate ion channel activity,
post NMDA receptor activation events, regulation of neurotransmitter levels,
regulation of synaptic transmission, synapse part ,gate channel activity.

Single Nucleotide Polymorphisms (snps) discussed in supplement are:rs10189857
rs1167898 rs11678980 rs18235539 rs182355396 rs186456786 rs186456786
rs186456786 rs5951458 rs61734410

Links to dbsnp for snps discussed in supplement:
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=101...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=10189857)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=116...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=1167898)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=116...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=11678980)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=182...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=18235539)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=182...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=182355396)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=186...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=186456786)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=595...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=5951458)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=617...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=61734410)
[https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=624...](https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=62422687)

~~~
searine
It is worth noting that these SNPs aren't causal, they are just associated.

The resolution of GWAS isn't at the level yet where we can pick out individual
changes that cause a phenotype. Instead we can detect that a chunk of the
genome is associated with a phenotype. These snps are like a street name, they
identify the region associated.

We need whole-genome sequence on a million-person scale to actually find the
causal variant. That will come with time.

------
zavi
Please don't post Dropbox links, the PDF downloads are unusable on Android.

~~~
jjtheblunt
Android is confused by PDFs ?

------
frgtpsswrdlame
I'll have to read this later since I'm at work but is there a layman's
explanation for how these studies distinguish environmental and genetic
influence? I don't see how you could accurately separate the two.

~~~
gwern
Not entirely sure what you mean: genes cause environments, and interact with
environments.

If you mean something like whether it's just picking up ancestry markers for
families which happen to be rich etc, there are a lot of methodological
components which try to minimize the more obvious ways of population
stratification affecting results.

The most iron-clad part of showing direct gene->trait causation is the 4
sibling-comparison studies, where you see whether you can predict the
difference between 2 siblings; as they have identical ancestries, families,
locations etc, their environments are near-identical in the first place, and
since meiosis at conception _randomizes_ genes between siblings, success in
sibling comparison shows the genes must be causal. IQ GWASes have always
passed the within-family test since Rietveld et al 2013, and this is no
exception.

~~~
frgtpsswrdlame
>If you mean something like whether it's just picking up ancestry markers for
families which happen to be rich etc, there are a lot of methodological
components which try to minimize the more obvious ways of population
stratification affecting results.

Yeah this is actually what I'm interested in.

>The most iron-clad part of showing direct gene->trait causation is the 4
sibling-comparison studies, where you see whether you can predict the
difference between 2 siblings; as they have identical ancestries, families,
locations etc, their environments are near-identical in the first place, and
since meiosis at conception randomizes genes between siblings, success in
sibling comparison shows the genes must be causal. IQ GWASes have always
passed the within-family test since Rietveld et al 2013, and this is no
exception.

Couldn't this still lead to an overstating of the effect? So two brothers John
and Jim have different builds due to genetics, John is a bit shorter and
stockier and Jim is a bit taller and leaner. When they play with each other as
children John usually wins when they wrestle and Jim usually wins when they
play basketball. They both like winning so in highschool John joins the
wrestling team and Jim joins the basketball team. Now if I do some gene
testing wizardry on them as adults and try to determine the difference in
basketball-skill I'll predict a large gap due to height genes and I'll get
one. But part of that skill gap is due to environment (4 years of basketball
practice) yet still getting attributed to genes.

~~~
gwern
> ...When they play with each other as children John usually wins when they
> wrestle and Jim usually wins when they play basketball...

No, this is still genetic causation (and something like this story is usually
what is invoked for why the heritability of intelligence increases with age:
more intelligent people seeking out niches which then encourage intelligence
further rather than preferring to veg out in front of the boobtube, leading
shared-environment to disappear while the permanent ongoing influence from
genetics leads to heritability increases).

What's the definition of causation? It's a 'difference which makes a
difference', or in Pearlean terms, if you reach in and do surgery on one node
in a causal network, the counterfactual difference.

So in your basketball example, what if we reached in with CRISPR, say, and
edited just the genes for builds in John to make him taller/leaner? What is
the counterfactual of our intervention on the node of genes? As he grows up
and becomes taller/leaner, now he still likes winning and playing with his
brother is an even challenge, so he joins the basketball team along with Jim
and they do well and keep playing and so on and so forth and your basketball
PGS predicts less or no difference between them (since we caused them to have
the same relevant genes) and indeed there is less or no difference; and if we
had instead edited the other way, it'd go the other way etc. Thus, causation.
That the causal pathway of the genes goes 'outside the skin', as some people
put it, makes no difference that makes a difference for this particular
question.

(A similar point applies to the 'nature of nurture' findings mentioned in Lee
et al 2018 and the two earlier papers. Are they genetic causation? Yes,
because if you counterfactually changed the genes and nothing but the genes,
you would get different outcomes. They are differences which make a
difference. They are, however, causal on things you didn't expect - eg edits
in children would cause gains in grandchildren rather than the children.)

~~~
frgtpsswrdlame
If what we're interested in is genetic causation then the relevant comparison
is to John if he was still shorter but joined the basketball team anyways. In
that case the variance between their skills would be less and yet no genes
were changed. That illustrates that the original difference wasn't due to
genetic but rather environmental factors.

>That the causal pathway of the genes goes 'outside the skin', as some people
put it, makes no difference that makes a difference for this particular
question.

When genes cause changes 'outside the skin' the way those outside changes
affect your skill are environmental changes by definition. For example you're
saying that in our current society, where you can choose your extracurricular
activity, the difference in their basketball-skill that's attributable to
genetics is _x_. But in a different society where high school basketball
practice was state mandated the difference in their basketball-skill that's
attributable to genetics would be _y_ where _y_ < _x_. The difference between
_x_ and _y_ can't be caused by genetics because we haven't changed any genes
so it shows that we were just misestimating genetic causation to begin with.

~~~
JamesBarney
You are using a definition of genetic causation that is not used by anyone in
the field of genetics. It sounds like your definition is "Is there any
hypothetical environment where the phenotypic expression of a gene could be
changed?" The answer is almost always yes.

Growth hormone influences height, imagine a world where everyone's level of
growth hormone is regulated. Suddenly all of these growth hormone influencing
genes no longer have any effect on height. By your definition growth hormone
does not genetically cause height because of this hypothetical. You could see
how using a definition is both incredibly restrictive as well as almost
impossible to measure, and therefore not a very useful definition.

~~~
frgtpsswrdlame
>You are using a definition of genetic causation that is not used by anyone in
the field of genetics.

That's worrying.

>It sounds like your definition is "Is there any hypothetical environment
where the phenotypic expression of a gene could be changed?" The answer is
almost always yes.

Sure but we don't even need a hypothetical environment where high school
basketball practice is state-mandated, we just need any hypothetical
environment where John and Jim both go to basketball practice and their genes
stay the same to see that what is labeled as genetic causation is actually
environmental. I mean are you telling me the entire field has no way to
distinguish a skill->environment->skill feedback effect from a genes->skill
effect?

I'd say that genes seem essentialist, they're something that defines you and
can't be changed but environment isn't that way, it's malleable and can be
changed. So take this example, we're gonna say at least 11% of IQ is genetic,
right? But if we pass some laws so that we have better teachers and smaller
class sizes and better remedial programs then what IQ is only 8% genetic? Or
even in the case that the laws help the top more and IQ expands to 14%
genetic. In that case it doesn't seem that our measurements of genetics
effects were accurately measuring the genetics at all, just environmental
effects that are hard to account for.

>You could see how using a definition is both incredibly restrictive as well
as almost impossible to measure, and therefore not a very useful definition.

Yes, I agree that what I'm saying would make genetic causation very difficult
to measure. But it's also the truth about what genetic causation is. Instead
we're just opting for what is easy to measure and labeling it as the thing
that is hard to measure. That's not right.

~~~
JamesBarney
Maybe if you gave some examples that would help.

Can you describe how you would even hypothetically measure your definition of
"genetic causation"? Could you give an example of a "gene causing" the
expression of an interesting trait in a way that is immune to environmental
changes?

You're looking for a gene that causes an outcome completely independently of
all environments. I don't think this exists for any interesting traits. Not to
mention how much effect a change has on a given trait is dependent on the
genetic make up of the population.

> But it's also the truth about what genetic causation is. No it's not,
> everyone who talks about genetic causation seriously use a different
> definition. I don't know why your own personal definition is better than the
> definition used by every single person who studies genetics.

~~~
frgtpsswrdlame
I would ditch the idea of widespread genetic correlations on complex traits,
switch to a method that describes what genes (and their interactions) actually
do to the human body. For example, this specific gene does x to a
neurotransmitter which can interact with y or z to cause changes like this or
that. (And I know it's actually more complicated than just a straight mapping
of gene X -> trait Y.)

With my method you can still say that no matter the environment gene x does
this thing which can interact with gene y or gene z or environmental factors
a, b, c in certain ways.

I think that proving intelligence is XX% genetic is basically meaningless
since we can't actually remove environmental effects and if I'm really honest
I think it's popularity in the culture is usually driven by spurious motives.

>No it's not, everyone who talks about genetic causation seriously use a
different definition. I don't know why your own personal definition is better
than the definition used by every single person who studies genetics.

Why do you think this is at the top of Hacker News? Because people's common
understanding of a title like:

 _New study shows that IQ is 11% genetic_

Is that at least 11% of their intelligence comes straight from their DNA, not
that actually we could change 11% to 5% or 8% or 17% or most any number we
want just by changing some laws or fortifying food or any number of
environmental changes. The popularity of genetics research in popular media
requires this bait-and-switch about what is actually being (mis) measured.

~~~
JamesBarney
> I would ditch the idea of widespread genetic correlations on complex traits,
> switch to a method that describes what genes (and their interactions)
> actually do to the human body. For example, this specific gene does x to a
> neurotransmitter which can interact with y or z to cause changes like this
> or that. (And I know it's actually more complicated than just a straight
> mapping of gene X -> trait Y.)

> With my method you can still say that no matter the environment gene x does
> this thing which can interact with gene y or gene z or environmental factors
> a, b, c in certain ways.

If you arguing that it is better to understand all of the casual pathways a
gene influences a trait than to not understand that, then I strongly agree. If
you are arguing that understanding which genes casually influence which
complex traits is useless until we know all of the casual pathways that gene
affect a trait then I'll have to disagree just as strongly.

> I think that proving intelligence is XX% genetic is basically meaningless
> since we can't actually remove environmental effects and if I'm really
> honest I think it's popularity in the culture is usually driven by spurious
> motives.

First proving what % of intelligence is heritable is not the purpose of
GWAS's. Twin studies are used for this, and they've found that intelligence is
highly heritable.(far higher than 11%)

Ways that GWAS's are useful without removing environment effects.

\- Embryo selection

\- Tests to figure out risk for certain diseases for preventative purposes

\- Used to figure out what are important pathways in complex traits/disease.
For instance if everyone with a certain defective enzyme has a 50% reduction
in heart attacks this could lead to a drug candidate

> New study shows that IQ is 11% genetic > Is that at least 11% of their
> intelligence comes straight from their DNA, not that actually we could
> change 11% to 5% or 8% or 17% or most any number we want just by changing
> some laws or fortifying food or any number of environmental changes. The
> popularity of genetics research in popular media requires this bait-and-
> switch about what is actually going on.

If you are arguing that some people(maybe even a lot) misunderstand the
definition of genetic causation in a similar way that you previously did, then
that might be true. But when any experts, or any study talks about genetic
causation they are using the definition the rest of us are using on the this
thread.

~~~
frgtpsswrdlame
>First proving what % of intelligence is heritable is not the purpose of
GWAS's.

And yet here we are on a thread about using a GWAS to prove what % of
intelligence is heritable.

>If you are arguing that some people(maybe even a lot) misunderstand the
definition of genetic causation in a similar way that you previously did, then
that might be true.

My understanding isn't past tense. Here, allow me to illustrate why this makes
no sense to me. Let's take what Gwern said above:

 _Are they genetic causation? Yes, because if you counterfactually changed the
genes and nothing but the genes, you would get different outcomes. They are
differences which make a difference._

But in my basketball example I could also say this:

 _Are they environmental causation? Yes, because if you counterfactually
changed the environment and nothing but the environment, you would get
different outcomes. They are differences which make a difference._

So we are going to take factors where both of those statements are true and
_still_ assert that they are genetically causal? That's incorrect.

>But when any experts, or any study talks about genetic causation they are
using the definition the rest of us are using on the this thread.

The 'rest of us' in this thread are definitely not using the same language you
use. Let's take a look at just the post author's comments:

\---

>The most iron-clad part of showing direct gene->trait causation is the 4
sibling-comparison studies

except it's not iron-clad at all and it doesn't show direct gene->trait
causation.

>where you see whether you can predict the difference between 2 siblings; as
they have identical ancestries, families, locations etc, their environments
are near-identical in the first place

Their environments are not near-identical.

>No, it doesn't. It merely tells us that with the data up to now, we've
reached 11% (up from, incidentally, ~0.3% just 5 years ago). It provides a
very loose lower bound on genes.

Except you're telling me that not only is a GWAS not useful for this purpose
but that even this number shouldn't be treated as a 'lower bound' but as a
potential identifier to further study the genes identified. It would seem that
this

>> Observational studies of this type cannot show causality >They can: sibling
comparisons.

Again, this quote appears to conflict with what you believe GWASs are capable
of.

\---

Again, why are these falsehoods being spread around? Because of an
(mis)understanding that 'genetic causation' as measured in the paper is not
manipulatable by the environment. Except that it actually is. And a
misunderstanding of what GWASs are good for.

>\- Embryo selection

No it's not. GWASs don't understand what they're measuring and label the
environmental as genetic biasing their measurements. Embryo selection is done
the old-fashioned way looking for specific genetic variants that we understand
through the use of other types of studies.

>\- Tests to figure out risk for certain diseases for preventative purposes

Look at the use of GWASs in identifying schizophrenia. They typically fail to
replicate. GWASs find genetic connections where none exist.

Take schizophrenia. It could be that we run a GWAS on schizophrenia and find
some genetic similarities. Then we look at these similarities and find one of
them is a cuddle gene. A cuddle gene what the heck? Well the cuddle gene makes
you want to cuddle which makes their mothers more likely to own pets to cuddle
which makes them more likely to own cats which increases their risk of
exposure to toxoplasmosis which increases their of schizophrenia. Is that a
genetic causation? Because the way genetic causation is _actually being used_
in this thread really doesn't lead to that conclusion. It leads to the idea
that the identified genes make you a little more unstable in a certain way,
not that we could totally eliminate that element of genetic causation by just
educating mothers.

------
oldgradstudent
In what sense is this a "discovery"?

Observational studies of this type cannot show causality, and the results have
not been confirmed by independent methods.

~~~
gwern
> Observational studies of this type cannot show causality

They can: sibling comparisons.

> the results have not been confirmed by independent methods.

They're tested out of sample many times (4 for sibling comparisons alone!),
and you can find many other papers successfully using the IQ GWASes. Belsky et
al 2018 just came out a few weeks ago, for a particularly good example testing
OP's PGS. (The PGS has been out since like March, so several papers have used
it.)

~~~
oldgradstudent
>> Observational studies of this type cannot show causality

>They can: sibling comparisons.

But then they get much lower concordance so they come up with various ad-hoc
hypotheses to explain it, instead of acknowledging the negative result.

This is an hypothesis generating paper, using a highly suspect methods. Not a
discovery.

------
cryoshon
taking all of the associations into account and making a polygenic predictor
score "does a lousy job predicting the outcome for any specific individual,
but it can explain 11 percent of the population-wide variation in years of
schooling."

only 11 percent. this tells us that the remainder is more likely to be
attributable to environmental factors.

in other words, even with a view of the genes, we would need to encourage
education more strenuously if we wanted to improve educational outcomes for
society.

~~~
gwern
> only 11 percent. this tells us that the remainder is more likely to be
> attributable to environmental factors.

No, it doesn't. It merely tells us that with the data up to now, we've reached
11% (up from, incidentally, ~0.3% just 5 years ago). It provides a very loose
lower bound on genes. Saying that is like saying, 'our software testing up to
now has only revealed bugs in 11 places, therefore, every other line of code
must be bug-free!' Even if you knew nothing about the actual heritability
estimates, one would think that finding so much so quickly would make one
suspect that there's a lot more to find...

~~~
cryoshon
there's always more to find, but consider that this model is leaving out the
environment entirely and its predictive value is even less than you might
think at first glance.

we know the environment impacts gene transcription, and we know that genetic
determinism (as far as outcome phenotypes) is not a thing. likewise, there may
be epigenetic factors at play which wouldn't be captured in a GWAS yet still
might (or might not) have an impact on outcomes.

it isn't a "the other lines of code are bug free" situation so much as a "we
expect there to be an abundance of bugs with undefined consequences outside of
the subset which we have examined which most likely outweigh the stuff we
found"

------
yk
From the discussion:

> However, theoretical projections that failed to consider heterogeneity of
> effect sizes were optimistic Our and others’ findings suggest that imperfect
> genetic correlation across cohorts will be the norm for phenotypes, such as
> educational attainment, that are environmentally contingent.

So it is somewhat worrying that genetics predict the clearly environmentally
contingent like educational attainment better than "cognitive performance."

> Our results also highlight two caveats to the use of the polygenic scores in
> research. First, our within-family analyses suggest that GWAS estimates may
> overstate the causal effect sizes: if educational attainment-increasing
> genotypes are associated with parental educational attainment-increasing
> genotypes, which are in turn associated with rearing environments that
> promote educational attainment, then failure to control for rearing
> environment will bias GWAS estimates.

That is a very complicated way of saying that some genes express themselves by
black skin, and these genes have a strong effect on funds available to the
school.

~~~
gwern
> So it is somewhat worrying that genetics predict the clearly environmentally
> contingent like educational attainment better than "cognitive performance."

I don't agree that schools are any more 'clearly environmentally contingent'
than intelligence, especially with the mandatory public schooling applicable
to all of the cohorts used.

> That is a very complicated way of saying that some genes express themselves
> by black skin

That's a remarkable assertion, considering that this dataset is made of 100%
white people, works on white siblings like Swedish twins, and the PGS is still
predictive when applied within a separate African-American dataset.

~~~
danieltillett
It would be remarkable if there was not some predictive value when applied to
AA datasets given the level of European ancestory in the AA population is
around 30%.

~~~
gwern
(Closer to 20%, and the attenuation of 85% is about what you would expect; we
already know that that's the usual level of decrease when you test PGSes in
AAs, and it goes to near-zero in African populations. It looks like it's not
an issue of entirely different causal variants or different environments, but
mostly LD tagging decay.)

~~~
danieltillett
The estimated range is 16.7% to 29% according to the fount of all wisdom
wikipedia [0].

0\.
[https://en.wikipedia.org/wiki/African_Americans](https://en.wikipedia.org/wiki/African_Americans)

