Things I Don’t Understand About Genetics (A Non-Exhaustive List)

A couple months ago the Genetic Association Consortium’s study on SNPs for intelligence raised an important question: should all of our genetics studies be performed by organizations whose acronyms are also amino acid codons? And aspartic acid? Really? Kind of a boring choice.

But while we’re figuring that out, can someone explain to me how polygenic inheritance works?

We have really strong evidence that intelligence is highly heritable – maybe 50% to 80%. But genome-wide association studies show very low contributions from any particular SNP:

The study found that the genetic markers with the strongest effects on educational attainment could each only explain two one-hundredths of a percentage point (0.02 percent). To put that figure into perspective, it is known from earlier research that the SNP with the largest effect on human height accounts for about 0.40 percent of the variation.

Combining the two million examined SNPs, the SSGAC researchers were able to explain about 2 percent of the variation in educational attainment across individuals, and anticipate that this figure will rise as larger samples become available.

Here’s my question. Things determined by a larger number of independent randomly varying processes should tend to vary less. Suppose at Casino A, you flip a coin and if it comes up heads they give you $5000 and if it comes up tails they give you nothing. But at Casino B, you flip 5000 coins, and get $1 for each coin that comes up heads and nothing for each coin that comes up tails.

Both games have the same minimum and maximum winnings ($0 and $5000), and both have the same average ($2500). But the variance will be very different. The winnings at Casino A will vary a lot; half the people will walk out with $5000 and the other half will walk out broke. The winnings at Casino B will vary surprisingly little: if I understand binomial distributions correctly, well under 1% of gamblers will walk out with less than $2400 or greater than $2600. Pretty much everyone goes home with something like $2500.

The more independent loci determine human intelligence, the less variation in human intelligence we expect to see relative to the total amount it is possible to vary. If the most important SNP explains 0.02%, then there are at least 5000 genes involved, which means, as in the example above, that less than 1% of people should differ more than 2% of total possible variability from the average.

But actually, people differ in intelligence a lot, and a lot of that difference seems to have a genetic component. This implies either that the total possible genetic variability in intelligence is huge – that the right genes could give you an IQ of 2500 or so, or that variability in intelligence isn’t simple and additive and random the way I’m modeling it here – or that I’m doing the math wrong, always a distinct possibility.

The easiest way to get out of this, other than accepting I am terrible at math and should be kept away from it, is to assume that lots of different genes for good intelligence are correlated. Maybe one population had reason to evolve high intelligence with lots of smart SNPs, and a second population didn’t. Then it would make complete sense that all the genes involved would co-vary. Unfortunately, there seems to be significant IQ variation within the same family, let alone within the same population group, so that fails pretty hard as an explanation.

Another possibility is to accept the whole mutational load idea – which allows for high correlations in goodness or badness of the entire genome. Unfortunately, this is the other idea in genetics which has been confusing me terribly over the past few months.

This has no trouble explaining correlations, but it does have trouble explaining why things aren’t more correlated. We should find the same people being very smart and very tall and very athletic and very healthy. I don’t doubt there are some correlations between these traits, but they don’t seem nearly as high as one might expect.

And the paternal age effect keeps being brought in to explain this, but I don’t get that one either. Suppose I have a kid at 60. My sperm and my DNA have had 60 years to accumulate deleterious mutations, so there’s more chance my kid will have low IQ or psychiatric disease or whatever. Fine. But suppose while I’m having a kid at 60, my twin brother has had a kid at age 20, and his kid had a kid at age 20, and his kid had a kid at age 20, so that his first great-grandchild is being born exactly the same time my first child is. Both my kid and his great-grandkid have had 60 years worth of cell dividings to accumulate mutations. Why should their risks of autism be any different just because his kid had those 60 years divided among three different people?

(does less frequent division of spermatogonia before puberty cause them to accumulate fewer mutations during that time? If so, shouldn’t three generations of people who have kids at 33 still accumulate 80% as many mutations as two generations of people who have kids at 50?)

I’ve heard evolution’s ability to eliminate people with bad genes used as an explanation here, but I don’t quite get it. For one thing, it seems unlikely that evolution can produce beneficial mutations at the same rate people accumulate deleterious mutations (10 per generation or so). And if we imagine two lineages of gradually deteriorating intelligence going on for 1000 years, the Lions That Selectively Eat Low-IQ People will have just as much opportunity to cull the members of the one that reproduces quickly as the one that reproduces slowly. And, if that were the explanation we should fail to see a paternal age effect in the absence of such lions (or be dysgenic as hell), but the effect has been demonstrated in our own society, which is relatively free of lions and of almost everything else that kills people before they can reproduce.

I know other people have blogs where they explain things and readers bask in their wisdom, but having a blog where I say how confused I am about stuff and readers explain it to me has always worked for me before and I have faith it will continue to do so.