there are known recent beneficial mutations in humans [...] a mutation allowing humans to digest milk in adulthood that became common in Europe around 10,000 years ago [...] At the time, people with this mutation left almost ten times as many descendants as people without it.
What does this actually mean? There seem to be two obvious interpretations. (1) “The expected number of surviving children of a person with the mutation was 10x that of a person without it.” That’s pretty hard to believe[1]. (2) “Over some unspecified number of generations the average number of descendants per person with the mutation was 10x that of someone without”. Isn’t that a really silly metric? (Consider a typical very-slightly-beneficial mutation. With probability modestly over 1⁄2 it gets fixed in the population, and then “people with this mutation left infinity times as many descendants as people without it”.) Not to mention that “at the time” then doesn’t make much sense.
What am I missing here?
[1] Most credible approximation to this that I can come up with: first lactose tolerance becomes widespread, then non-human milk becomes an important food source, then lactose intolerance becomes a big big handicap and people without it could easily have 10x fewer surviving offspring. But here the real heavy lifting is done by whatever process gets lactose tolerance widespread in the first place, and there’s no explanation for the alleged 10x advantage during that period.
If you got this from a popularization you may have run into a miscommunication about odds ratios versus relative rates? This is one of those known problems that will be around for a long time because its a subtle point and being wrong on the subtle point helps people score “OMG that’s amazing!” points that are rhetorically effective (and get higher click-through when put in a headline) but which are not very accurate.
I have good library access. Send me a PM with your email and I’ll email you the PDF if you want to check the original source for precise numbers :-)
Reading that paper, I feel like a dog being shown a card trick … but gjm hypothesises a reporter being told “almost 10% more” (upper bound of likely selection coefficient ~0.97 edit: ~0.097) and hearing “almost ten times more”. This is alarmingly plausible.
What does this actually mean? There seem to be two obvious interpretations. (1) “The expected number of surviving children of a person with the mutation was 10x that of a person without it.” That’s pretty hard to believe[1]. (2) “Over some unspecified number of generations the average number of descendants per person with the mutation was 10x that of someone without”. Isn’t that a really silly metric? (Consider a typical very-slightly-beneficial mutation. With probability modestly over 1⁄2 it gets fixed in the population, and then “people with this mutation left infinity times as many descendants as people without it”.) Not to mention that “at the time” then doesn’t make much sense.
What am I missing here?
[1] Most credible approximation to this that I can come up with: first lactose tolerance becomes widespread, then non-human milk becomes an important food source, then lactose intolerance becomes a big big handicap and people without it could easily have 10x fewer surviving offspring. But here the real heavy lifting is done by whatever process gets lactose tolerance widespread in the first place, and there’s no explanation for the alleged 10x advantage during that period.
The “ten times” is from the referenced NYT article. It could do with tracking to the source, yes.
edit: This appears to be the original paper, and it’s paywalled. But I’ll keep looking for a copy.
If you got this from a popularization you may have run into a miscommunication about odds ratios versus relative rates? This is one of those known problems that will be around for a long time because its a subtle point and being wrong on the subtle point helps people score “OMG that’s amazing!” points that are rhetorically effective (and get higher click-through when put in a headline) but which are not very accurate.
I have good library access. Send me a PM with your email and I’ll email you the PDF if you want to check the original source for precise numbers :-)
Reading that paper, I feel like a dog being shown a card trick … but gjm hypothesises a reporter being told “almost 10% more” (upper bound of likely selection coefficient ~0.97 edit: ~0.097) and hearing “almost ten times more”. This is alarmingly plausible.
Correction: 0.097, not 0.97.
I can access it. If you PM me your email address, I can send it to you.