Sasha Gusev Profile picture
Jan 29 11 tweets 4 min read Read on X
So this is pretty typical of the low-information content you get from the genetic racists. The majority of this post is just blather but there is one (1) specific claim about genetics: that the molecular genetic contribution to IQ keeps going up every year. This is false. A 🧵:
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The first study in 2011 into the heritability of IQ using molecular genetic methods found moderately high estimates 40-51%. But this approach was flawed technically (estimator bounds and population structure) and conceptually (environmental confounding). Image
Fast forward to 2023, using hundreds of thousands of people from the UK Biobank, Williams et al. [] ran a battery of analyses to refine a high-quality IQ estimate. The heritability ... 0.20 (with very precise error). pubmed.ncbi.nlm.nih.gov/36378351/
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But this doesn't address the conceptual issue of environmental confounding. For that, Howe et al. used a large-scale within-family analysis, which does a much better job of isolating the genetic component from shared environment. Their estimate of the heritability ... 0.14! Image
So we've gone from 51% to 20% to 14% as the field has learned how to apply these methods more precisely and address confounding. Researchers that raised concerns of environmental confounds and stratification were proven right, and it's unlikely that we've resolved all the issues.
This trend is even more extreme for Educational Attainment, an easier to study trait with more practical relevance. Initial studies had estimates of 22% heritability which decreased to ~15% as better methods and more representative cohorts were applied. Image
When Howe et al. finally employed a proper within-family analysis their estimate of the heritability was ... just 4% (with a tight error bound). That's right, the *entire* common genetic contribution to educational attainment, a major status-driving factor, is a rounding error. Image
So the technical point is flat out wrong. And this style of argument mirrors a general trend. Charles Murray has been promising that his views will be vindicated in "just five years" since 1994!

Steve Hsu has been arguing that a 60% accurate genetic predictor is just around the corner since 2011, and last year declared himself vindicated! (As we just saw, the GWAS heritability of IQ is <14%, it cannot possibly reach 60%)

The shell game they play is: (1) claim that there's *lots* of evidence out there; (2) present one or two sketchy correlations based on bad methods; (3) promise that the better results are just around the corner. In the real world, their position keeps losing. /fin
Sailer tends to disappear whenever he is addressed directly so I'm not hoping for a response. Maybe in a day we'll get another story about sports or movies. But here are a few more unaddressed errors in the whole race/genes/IQ/outcomes project:

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More from @SashaGusevPosts

Jan 29
The racists in Stancil's replies have started appealing to "scientific consensus". So let's look at what the consensus of *high-quality evidence* is on genetic racism. A 🧵:
On genetics/race/behavior, over a hundred population geneticists denounced Nick Wade's A Troublesome Inheritance (a sort of genetic racism catechism). Their conclusion: "there is no support from the field of population genetics for Wade’s conjectures"

cehg.stanford.edu/sites/g/files/…
David Reich, a preeminent population geneticist, went on to write an entire book on the topic of genetic ancestry. His conclusion: "the ancient DNA revolution ... is fueling a critique of race ... Mixture is fundamental to who we are" Image
Read 8 tweets
Jan 27
Let me expand on this since I think it's a useful lens through which think about heritability estimates. When we talk about "dominance" we're really talking about genetic effects that deviate from additivity: an effect only kicks in when you have both/neither allele. A 🧵:
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Most common traits in humans are driven by tens/hundreds of thousands of genetic variants of small effect, so we are interested in dominance heritability i.e. the contribution of *all* of these non-additive effects together, which we can contrast with the additive contribution.
There's a long-standing debate over the extent and causes of dominance effects in human traits, summarized well in a recent study of Palmer et al []. Certainly we see plenty of non-additivity at the biological level, but what about genetic effects? science.org/doi/10.1126/sc…
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Read 10 tweets
Jan 27
It's the year 2024 and people are still publishing twin studies with massive dominance heritability estimates -- completely implausible and not observed with any other method -- and zero data availability. Why are we still doing this?
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Limitations: someone looked at environmental assumption violations 24 years ago so we never have to think about it again. Also, we won't even mention AC interactions, and we'll cite Purcell 2002 in a weird way so no one can find it. What do you call this act? Behavioral Genetics!

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Back on earth, the mean dominance heritability using molecular methods across 1,000 traits in the UK Biobank was ... 0.00076 [Palmer et al. 2023 Science].

gusevlab.org/projects/hsq/#…
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Read 5 tweets
Jan 26
I've written up a "crash course" on population genetics parameters useful for thinking about recent selection, heritability, and group differences (as part of a longer write-up on these concepts).



I'll summarize the key points here 🧵: gusevlab.org/projects/hsq/#…
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A preface: if you're generally interested in population genetics it's better to learn from first principles, and I've linked some useful resources to that end (many free). In particular (spoiler) recent evolution excludes some of the more interesting concepts and personalities. Image
But one downside of the general approach is that it can be hard to get a feel for real time (for example when populations are modeled in terms of 4Ne\mu). Here we'll fix three parameters based on data: time (t=65k years), population size (Ne=10k), and selection (s=~10^-4).
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Read 18 tweets
Jan 18
We discussed Duffy et al. [] in journal club. Neat approach integrating multiple sources of human genetic evidence to prioritize potential drug targets. Some thoughts 🧵:nature.com/articles/s4158…
The basic idea: approved drugs are enriched for targets with multiple lines of genetic evidence: clinical, rare coding, and common GWAS. Let's put them together. (See also: Sadler, ; Minikel, ; Nelson, ; etc). pubmed.ncbi.nlm.nih.gov/37492104/
medrxiv.org/content/10.110…
pubmed.ncbi.nlm.nih.gov/26121088/
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They wrangle a ton of data and train a logistic regression to combine features into a "priority score" for gene-disease target prioritization. Even though the number of drug indications for training was small (just 282) the resulting score is enriched for approved targets! Image
Read 10 tweets
Jan 12
Two new genetic studies of (environmentally confounded) behavioral phenotypes: Income (yes) and Educational Attainment in East Asian populations. What did they find? A 🧵:

[]
[]biorxiv.org/content/10.110…
nature.com/articles/s4156…
As I've argued before () these are valid phenotypes to study but the emphasis needs to be on estimating and interpreting causal parameters, not environmental correlations. That means focusing on within-family results. So let's do that for income first.gusevlab.org/projects/hsq/#…
The income GWAS used three phenotypes (+ parental income in one study), almost all self-reported, across multiple European countries (sample sizes below).

The direct genetic prediction of income (estimated in sibs) was ~1%, so that gives a sense of how little genetics matters.
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Read 17 tweets

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