The original discussion was about how personality traits and social outcomes could behave fundamentally differently from biological traits when it comes to genetics. So this isn’t necessarily meant to apply to disease risks.
Well you brought up depression. But anyway, all my questions apply to personality traits as well.
..… To rephrase / explain how confused I am about what you’re trying to tell me: It kinda sounds like you’re saying “If some trait is strongly determined by one big chunk of genes, then you won’t be able to see how some other chunk affects the trait.”. But this can’t explain missing heritability! In this scenario, none of the heritability is even from the second chunk of genes in the first place! Or am I missing something?
Because if some of the heritability is from the second chunk, that means that for some pairs of people, they have roughly the same first chunk but somewhat different second chunks; and they have different traits, due to the difference in second chunks. If some amount of heritability is from the second chunk, then to that extent, there’s a bunch of pairs of people whose trait differences are explained by second chunk differences. If you made a PGS, you’d see these pairs of people and then you’d find out how specifically the second chunk affects the trait.
I could be confused about some really basic math here, but yeah, I don’t see it. Your example for how the gradient doesn’t flow seems to say “the gradient doesn’t flow because the second chunk doesn’t actually affect the trait”.
If some amount of heritability is from the second chunk, then to that extent, there’s a bunch of pairs of people whose trait differences are explained by second chunk differences. If you made a PGS, you’d see these pairs of people and then you’d find out how specifically the second chunk affects the trait.
This only applies if the people are low in the first chunk and differ in the second chunk. Among the people who are high in the first chunk but differ in the second chunk, the logarithm of their trait level will be basically the same regardless of the second chunk (because the logarithm suppresses things by the total), so these people will reduce the PGS coefficients rather than increasing the PGS coefficients. When you create the PGS, you include both groups, so the PGS coefficients will be downwards biased relative to γ.
Among the people who are high in the first chunk but differ in the second chunk, the logarithm of their trait level will be basically the same regardless of the second chunk (because the logarithm suppresses things by the total), so these people will reduce the PGS coefficients rather than increasing the PGS coefficients
It would decrease the narrowsense (or additive) heritability, which you can basically think of as the squared length of your coefficient vector, but it wouldn’t decrease the broadsense heritability, which is basically the phenotypic variance in expected trait levels you’d get by shuffling around the genotypes. The missing heritability problem is that when we measure these two heritabilities, the former heritability is lower than the latter.
Why not? Shuffling around the second chunk, while the first chunk is already high, doesn’t do anything, and therefore does not contribute phenotypic variance to broadsense heritability.
Ok, more specifically, the decrease in the narrowsense heritability gets “double-counted” (after you’ve computed the reduced coefficients, those coefficients also get applied to those who are low in the first chunk and not just those who are high, when you start making predictions), whereas the decrease in the broadsense heritability is only single-counted. Since the single-counting represents a genuine reduction while the double-counting represents a bias, it only really makes sense to think of the double-counting as pathological.
Ah… ok I think I see where that’s going. Thanks! (Presumably there exists some standard text about this that one can just link to lol.)
I’m still curious whether this actually happens.… I guess you can have the “propensity” be near its ceiling.… (I thought that didn’t make sense, but I guess you sometimes have the probability of disease for a near-ceiling propensity be some number like 20% rather than 100%?) I guess intuitively it seems a bit weird for a disease to have disjunctive causes like this, but then be able to max out at the risk at 20% with just one of the disjunctive causes? IDK. Likewise personality...
(Presumably there exists some standard text about this that one can just link to lol.)
I don’t think so.
I’m still curious whether this actually happens.… I guess you can have the “propensity” be near its ceiling.… (I thought that didn’t make sense, but I guess you sometimes have the probability of disease for a near-ceiling propensity be some number like 20% rather than 100%?) I guess intuitively it seems a bit weird for a disease to have disjunctive causes like this, but then be able to max out at the risk at 20% with just one of the disjunctive causes? IDK. Likewise personality...
For something like divorce, you could imagine the following causes:
Most common cause is you married someone who just sucks
… but maybe you married a closeted gay person
… or maybe your partner was good but then got cancer and you decided to abandon them rather than support them through the treatment
The genetic propensities for these three things are probably pretty different: If you’ve married someone who just sucks, then a counterfactually higher genetic propensity to marry people who suck might counterfactually lead to having married someone who sucks more, but a counterfactually higher genetic propensity to marry a closeted gay person probably wouldn’t lead to counterfactually having married someone who sucks more, nor have much counterfactual effect on them being gay (because it’s probably a nonlinear thing), so only the genetic propensity to marry someone who sucks matters.
In fact, probably the genetic propensity to marry someone who sucks is inversely related to the genetic propensity to divorce someone who encounters hardship, so the final cause of divorce is probably even more distinct from the first one.
(Presumably there exists some standard text about this that one can just link to lol.)
I don’t think so.
How confident are you / why do you think this? (It seems fairly plausible given what I’ve heard about the field of genomics, but still curious.) E.g. “I have a genomics PhD” or “I talk to geneticists and they don’t really know about this stuff” or “I follow some twitter stuff and haven’t heard anyone talk about this”.
In fact, probably the genetic propensity to marry someone who sucks is inversely related to the genetic propensity to divorce someone who encounters hardship, so the final cause of divorce is probably even more distinct from the first one.
Ok I’m too tired to follow this so I’ll tap out of the thread for now.
The original discussion was about how personality traits and social outcomes could behave fundamentally differently from biological traits when it comes to genetics. So this isn’t necessarily meant to apply to disease risks.
Well you brought up depression. But anyway, all my questions apply to personality traits as well.
..… To rephrase / explain how confused I am about what you’re trying to tell me: It kinda sounds like you’re saying “If some trait is strongly determined by one big chunk of genes, then you won’t be able to see how some other chunk affects the trait.”. But this can’t explain missing heritability! In this scenario, none of the heritability is even from the second chunk of genes in the first place! Or am I missing something?
Some of the heritability would be from the second chunk of genes.
To the extent that the heritability is from the second chunk, to that extent the gradient does flow, no?
Why?
Because if some of the heritability is from the second chunk, that means that for some pairs of people, they have roughly the same first chunk but somewhat different second chunks; and they have different traits, due to the difference in second chunks. If some amount of heritability is from the second chunk, then to that extent, there’s a bunch of pairs of people whose trait differences are explained by second chunk differences. If you made a PGS, you’d see these pairs of people and then you’d find out how specifically the second chunk affects the trait.
I could be confused about some really basic math here, but yeah, I don’t see it. Your example for how the gradient doesn’t flow seems to say “the gradient doesn’t flow because the second chunk doesn’t actually affect the trait”.
This only applies if the people are low in the first chunk and differ in the second chunk. Among the people who are high in the first chunk but differ in the second chunk, the logarithm of their trait level will be basically the same regardless of the second chunk (because the logarithm suppresses things by the total), so these people will reduce the PGS coefficients rather than increasing the PGS coefficients. When you create the PGS, you include both groups, so the PGS coefficients will be downwards biased relative to γ.
Wouldn’t this also decrease the heritability?
It would decrease the narrowsense (or additive) heritability, which you can basically think of as the squared length of your coefficient vector, but it wouldn’t decrease the broadsense heritability, which is basically the phenotypic variance in expected trait levels you’d get by shuffling around the genotypes. The missing heritability problem is that when we measure these two heritabilities, the former heritability is lower than the latter.
Why not? Shuffling around the second chunk, while the first chunk is already high, doesn’t do anything, and therefore does not contribute phenotypic variance to broadsense heritability.
Ok, more specifically, the decrease in the narrowsense heritability gets “double-counted” (after you’ve computed the reduced coefficients, those coefficients also get applied to those who are low in the first chunk and not just those who are high, when you start making predictions), whereas the decrease in the broadsense heritability is only single-counted. Since the single-counting represents a genuine reduction while the double-counting represents a bias, it only really makes sense to think of the double-counting as pathological.
Ah… ok I think I see where that’s going. Thanks! (Presumably there exists some standard text about this that one can just link to lol.)
I’m still curious whether this actually happens.… I guess you can have the “propensity” be near its ceiling.… (I thought that didn’t make sense, but I guess you sometimes have the probability of disease for a near-ceiling propensity be some number like 20% rather than 100%?) I guess intuitively it seems a bit weird for a disease to have disjunctive causes like this, but then be able to max out at the risk at 20% with just one of the disjunctive causes? IDK. Likewise personality...
I don’t think so.
For something like divorce, you could imagine the following causes:
Most common cause is you married someone who just sucks
… but maybe you married a closeted gay person
… or maybe your partner was good but then got cancer and you decided to abandon them rather than support them through the treatment
The genetic propensities for these three things are probably pretty different: If you’ve married someone who just sucks, then a counterfactually higher genetic propensity to marry people who suck might counterfactually lead to having married someone who sucks more, but a counterfactually higher genetic propensity to marry a closeted gay person probably wouldn’t lead to counterfactually having married someone who sucks more, nor have much counterfactual effect on them being gay (because it’s probably a nonlinear thing), so only the genetic propensity to marry someone who sucks matters.
In fact, probably the genetic propensity to marry someone who sucks is inversely related to the genetic propensity to divorce someone who encounters hardship, so the final cause of divorce is probably even more distinct from the first one.
How confident are you / why do you think this? (It seems fairly plausible given what I’ve heard about the field of genomics, but still curious.) E.g. “I have a genomics PhD” or “I talk to geneticists and they don’t really know about this stuff” or “I follow some twitter stuff and haven’t heard anyone talk about this”.
Ok I’m too tired to follow this so I’ll tap out of the thread for now.
Thanks again!
I talk to geneticists (mostly on Twitter, or rather now BlueSky) and they don’t really know about this stuff.