My take on missing heritability is summed up in Heritability: Five Battles, especially §4.3-4.4. Mental health and personality have way more missing heritability than things like height and blood pressure. I think for things like height and blood pressure etc., you’re limited by sample sizes and noise, and by SNP arrays not capturing things like copy number variation. Harris et al. 2024 says that there exist methods to extract CNVs from SNP data, but that they’re not widely used in practice today. My vote would be to try things like that, to try to squeeze a bit more predictive power in the cases like height and blood pressure where the predictors are already pretty good.
On the other hand, for mental health and personality, there’s way more missing heritability, and I think the explanation is non-additivity. I humbly suggest my §4.3.3 model as a good way to think about what’s going on.
If I were to make one concrete research suggestion, it would be: try a model where there are 2 (or 3 or whatever) latent schizophrenia subtypes. So then your modeling task is to jointly (1) assign each schizophrenic patient to one of the 2 (or 3 or whatever) latent subtypes, and (2) make a simple linear SNP predictor for each subtype. I’m not sure if anyone has tried this already, and I don’t personally know how to solve that joint optimization problem, but it seems like the kind of problem that a statistics-savvy person or team should be able to solve.
I do definitely think there are multiple disjoint root causes for schizophrenia, as evidenced for example by the fact that some people get the positive symptoms without the cognitive symptoms, IIUC. I have opinions (1,2) about exactly what those disjoint root causes are, but maybe that’s not worth getting into here. Ditto with autism having multiple disjoint root causes—for example, I have a kid who got an autism diagnosis despite having no sensory sensitivities, i.e. the most central symptom of autism!! Ditto with extroversion, neuroticism, etc. having multiple disjoint root causes, IMO.
Note that my suggestion (“…try a model where there are 2 (or 3 or whatever) latent schizophrenia subtypes. So then your modeling task is to jointly (1) assign each schizophrenic patient to one of the 2 (or 3 or whatever) latent subtypes, and (2) make a simple linear SNP predictor for each subtype…”)
…is a special case of @TsviBT’s suggestion (“what about small but not tiny circuits?”).
Namely, my suggestion is the case of the following “small but not tiny circuit”: X OR Y […maybe OR Z etc.].
This OR circuit is nice in that it’s a step towards better approximation almost no matter what the true underlying structure is. For example, if there’s a U-shaped quadratic dependency, the OR can capture whether you’re on the descending vs ascending side of the U. Or if there’s a sum of two lognormals, one is often much bigger than the other, and the OR can capture which one it is. Or whatever.
Thinking about it more, I guess the word “disjoint” in “disjoint root causes” in my comment is not quite right for schizophrenia and most other cases. For what little it’s worth, here’s the picture that was in my head in regards to schizophrenia:
The details don’t matter too much but see 1,2. The blue blob is a schizophrenia diagnosis. The purple arrows represent some genetic variant that makes cortical pyramidal neurons generally less active. For someone predisposed to schizophrenia mainly due to “unusually trigger-happy 5PT cortical neurons”, that genetic variant would be protective against schizophrenia. For someone predisposed to schizophrenia mainly due to “deficient cortex-to-cortex communication”, the same genetic variant would be a risk factor.
The X OR Y model would work pretty well for this—it would basically pull apart the people towards the top from the people towards the right. But I shouldn’t have said “disjoint root causes” because someone can be in the top-right corner with both contributory factors at once.
(I’m very very far from a schizophrenia expert and haven’t thought this through too much. Maybe think of it as a slightly imaginary illustrative example instead of a confident claim about how schizophrenia definitely works.)
My take on missing heritability is summed up in Heritability: Five Battles, especially §4.3-4.4. Mental health and personality have way more missing heritability than things like height and blood pressure. I think for things like height and blood pressure etc., you’re limited by sample sizes and noise, and by SNP arrays not capturing things like copy number variation. Harris et al. 2024 says that there exist methods to extract CNVs from SNP data, but that they’re not widely used in practice today. My vote would be to try things like that, to try to squeeze a bit more predictive power in the cases like height and blood pressure where the predictors are already pretty good.
On the other hand, for mental health and personality, there’s way more missing heritability, and I think the explanation is non-additivity. I humbly suggest my §4.3.3 model as a good way to think about what’s going on.
If I were to make one concrete research suggestion, it would be: try a model where there are 2 (or 3 or whatever) latent schizophrenia subtypes. So then your modeling task is to jointly (1) assign each schizophrenic patient to one of the 2 (or 3 or whatever) latent subtypes, and (2) make a simple linear SNP predictor for each subtype. I’m not sure if anyone has tried this already, and I don’t personally know how to solve that joint optimization problem, but it seems like the kind of problem that a statistics-savvy person or team should be able to solve.
I do definitely think there are multiple disjoint root causes for schizophrenia, as evidenced for example by the fact that some people get the positive symptoms without the cognitive symptoms, IIUC. I have opinions (1,2) about exactly what those disjoint root causes are, but maybe that’s not worth getting into here. Ditto with autism having multiple disjoint root causes—for example, I have a kid who got an autism diagnosis despite having no sensory sensitivities, i.e. the most central symptom of autism!! Ditto with extroversion, neuroticism, etc. having multiple disjoint root causes, IMO.
Good luck! :)
Note that my suggestion (“…try a model where there are 2 (or 3 or whatever) latent schizophrenia subtypes. So then your modeling task is to jointly (1) assign each schizophrenic patient to one of the 2 (or 3 or whatever) latent subtypes, and (2) make a simple linear SNP predictor for each subtype…”)
…is a special case of @TsviBT’s suggestion (“what about small but not tiny circuits?”).
Namely, my suggestion is the case of the following “small but not tiny circuit”: X OR Y […maybe OR Z etc.].
This OR circuit is nice in that it’s a step towards better approximation almost no matter what the true underlying structure is. For example, if there’s a U-shaped quadratic dependency, the OR can capture whether you’re on the descending vs ascending side of the U. Or if there’s a sum of two lognormals, one is often much bigger than the other, and the OR can capture which one it is. Or whatever.
Thinking about it more, I guess the word “disjoint” in “disjoint root causes” in my comment is not quite right for schizophrenia and most other cases. For what little it’s worth, here’s the picture that was in my head in regards to schizophrenia:
The details don’t matter too much but see 1,2. The blue blob is a schizophrenia diagnosis. The purple arrows represent some genetic variant that makes cortical pyramidal neurons generally less active. For someone predisposed to schizophrenia mainly due to “unusually trigger-happy 5PT cortical neurons”, that genetic variant would be protective against schizophrenia. For someone predisposed to schizophrenia mainly due to “deficient cortex-to-cortex communication”, the same genetic variant would be a risk factor.
The X OR Y model would work pretty well for this—it would basically pull apart the people towards the top from the people towards the right. But I shouldn’t have said “disjoint root causes” because someone can be in the top-right corner with both contributory factors at once.
(I’m very very far from a schizophrenia expert and haven’t thought this through too much. Maybe think of it as a slightly imaginary illustrative example instead of a confident claim about how schizophrenia definitely works.)