To understand why this matters, we usually take height as an
example of a polygenic trait. There have been many SNP’s (smallest units) found
to be “associated with” height. Even
though they only have enough to account for 15% of the variance at this point,
it was enough to predict that Shawn Bradley
would be well above-average in height from his DNA alone. (Former NBA. 7'6") But all of these
discoveries are from Northern European samples.
When you run the same tests on people of African descent, they show very
few of those SNPs associated with height.
They have so few, in fact that the test will predict that they are very
short indeed, less than five feet, even if they are seven feet tall. Africans have different genes making them
taller. A word on the side about these many genes that contribute to
height. They are not so much of the form
“make the shinbone a little longer,” as more general health items such as
digestion and energy conversion, or when hormones activate and when they stop. A
fair number may be primarily prenatal influence.
A further word about “associated with.” Genes often come in
long strings on the chromosome from one generation to the next, breaking up
only gradually over the centuries, so that we even use this rate of breaking up
as a measure of how long ago it was inherited. Therefore, everything on that particular
chain will be “associated with” height even if only a couple of them actually
have anything to do with height. An
example I have heard twice and therefore figure must be common, are the
genes “associated with” being able to manipulate chopsticks. Clearly, anything more common in East Asian
genes is going to be a positive hit for that association, even though almost
none of those genes have anything to do with the skill. This is true for many kinds of research,
which is why we say “correlation is not causation.” Social scientists, particularly in education
still seem unable to grasp this in practice, however well they can recite it in
theory.
The practical effect is that sometimes preventive
interventions target a particular mechanism, so that a medication might be
protective. Yet if that medication doesn’t work on you, you are just taking it
uselessly – with whatever side effects it produces. Simple accurate prediction
is also useful. If you learn your child has a high polygenic risk score for
schizophrenia, you put double and triple effort into making sure she doesn't touch
marijuana until she’s thirty-five (probably twenty-five for males). Chinese-Americans
may end up doing well despite their low numbers here, because the Chinese are
going to be doing that work on their own.
But it’s going to be a long slog in Africa. Not only are there not a high percentage of
customers there (they will likely have to depend on what we learn from
African-American samples), but the genetic variance is so great there that the
sampling has to be ten or a hundred times as great. The difference between Khoi-San and Igbo, or
the Kikuyu and Tswana are more than four times the genetic distance between me
and Australian aborigines, and there’s dozens of those tribes, whose responses
to medication are going to vary widely. Stray fact: Africa is large, but
dividing it into five easy categories is fairly useful in terms of
history. East Africa is very different from
West Africa. North Africa is very different
from southern Africa, and central Africa is distinct as well. It’s a shorthand starting point to prevent
overgeneralization.
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