Sasha Gusev Profile picture
Jan 29, 2024 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 🧵:
Image
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/
Image
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:

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Sasha Gusev

Sasha Gusev Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @SashaGusevPosts

Jan 20
How population stratification makes environments look like genes. A short 🧵: Image
Start with two populations undergoing neutral drift but with no frequency differences on the alleles that influence the trait (i.e. no genetically causal population differences). Image
Generate a phenotype that differs slightly between the populations for entirely non-genetic reasons (i.e. a difference in the environmental means). Drift + environmental differences = population stratification. Image
Read 7 tweets
Jan 15
This account is a firehose of quantitative racism but it is worth re-iterating that: if a trait like skin color is caused by genes, and society determines outcomes based on skin color, then -- yes -- those outcomes will also be heritable. This is heritability 101! Image
The fact that these guys were able to cook up a simulation that "disproved" a hypothesis that any intro genetics student knows is TRUE is a testament to how much nonsense people can get up to on here with a poor grasp of R and ggplot. Image
Image
Image
This is in fact such a basic example that it is used repeatedly when discussing and interpreting heritability. Here is Jencks 1972 providing the example with red-haired children prevented from going to school, and generalizing to sex, skin color, etc. Image
Image
Read 7 tweets
Nov 24, 2024
I wrote about the National Institutes of Health and the various serious and unserious proposals for NIH reform that have been floating around. It is important to understand how this agency actually functions and point criticism at the right problems. A short 🧵: Image
The vast majority of the NIH budget goes towards funding research proposals in some form. I walk through the grant review process but the takeaway is that proposals are evaluated by groups of scientists on importance + rigor and most proposals *do not get funded*. Image
Image
Even though this process has led to highly successful science, there are some problems.

1. Beyond a certain level, grant scores are not predictive of the actual scientific output. Meaning a lot of review discussion is spent on essentially arbitrary factors. Image
Read 9 tweets
Nov 2, 2024
I wrote about the evidence for selective sweeps from genomic data over the past 50,000 years. A few highlights: Image
Accurately detecting loci under selection is complicated by three main factors: neutral drift (which adds noise to allele frequencies), gene flow (which can hide or falsify frequency changes), and background selection (which induces more drift and temporal covariance). Image
Image
Image
Image
Many large studies have searched for selection with modern and ancient data, typically finding few examples. Palamara 2018 found 12 loci w/ modern data; Irving-Pease 2024 found 21 loci w/ aDNA coalescent model; Le 2022 found 25 w/ an aDNA mixture model. Most for pigment/immunity. Image
Read 11 tweets
Oct 30, 2024
One thing that has been difficult to understand from the election coverage is how Trump's policies are going to impact *me*, a rootless cosmopolitan and an Ivy League professor. Let's take a look:
I'm on the right side of this chart, so Trump is going to blow up the deficit to give me a tax cut, while 40% of households get effective tariff hikes. Is this populism? Image
Elon Musk is promising some "temporary hardship" that Trump has planned as part of a Great Leap Forward. That hasn't turned out well in the past, but my job is secure and soft so I -- like Musk -- will be the least affected. Image
Read 10 tweets
Sep 16, 2024
Really interesting new paper from Akbari et al. identifying a lot more selection in ancient DNA than previous approaches. I think it gets at three core challenges for this type of analysis where our understanding is still limited. 🧵
The core idea is to model allele frequency in ancient DNA as a function of time. If frequency has changed more than would be expected from drift and gene flow, that may be evidence of selection. Modeling drift/gene flow is hard, and the authors develop a new mixed model to do it.

Image
Image
Image
The random effect assumes that genetic relatedness can fully model the excess variance. This has often worked well in modern GWAS, but not always. See: [] for examples where such a model still produces inflated statistics. ncbi.nlm.nih.gov/pmc/articles/P…
Image
Read 11 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(