Is hereditarianism wrong yet?
What I think are the best arguments against the importance of genes
My previous post about hereditarianism was much more successful than I expected. It prompted many comments, including very detailed ones by Braeann Danads, Unboxing Politics, and even Sasha Gusev and Jay Joseph. We all agreed that within-family GWAS is underpowered so the core debate was about whether within-family SNP heritability studies (which show low heritability) are more credible than pedigree studies (which show high heritability).
Gusev is a statistical geneticist so the Sun Tzu move from him in a debate like this is to make everything about the technical details of the models used in specific papers, pointing out flaws and limitations in the ones he doesn’t like and pulling out new ones he does like. For example, in this paper MZ twins reared apart correlate 0.78 for general cognitive ability, MZs reared together 0.8, DZs reared apart 0.32, and DZs reared together 0.22. My reading of this is that growing up in the same family doesn’t make either MZs or DZs more similar and MZs are over twice as similar, so intelligence looks quite heritable. This is also what the authors conclude with formal modeling (Table 3, heritability=81%). But Gusev says the real story is that DZAs are more similar than DZTs (the difference is actually not statistically significant) and an analysis explicitly done to show that assuming non-additive genetic effects doesn’t add much to the model (Table A1) produces nonsense estimates so the study is “a complete mess”. On the other hand, he didn’t engage very much with the IMO very plausible argument that sib-regression and RDR miss some kind of important genetic variation, and the fact that the lack of similarity in adoptees makes strong shared environmental effects rather unlikely and this is hard to explain by some issue of the design.
Normally it’s great when people argue with numbers instead of calling each others racists and Marxist wokes but in this case it’s starting to look like arguing about social psychology or brain imaging or candidate genes with numbers: technically, there are numbers in molecular genetics but there is something wrong with them. For example, this recent paper found a 74.6% heritability of cognitive performance using sib-regression, one of Gusev’s preferred methods. Some hereditarians celebrated this but I’m not really buying it. The study used six cohorts, but the results didn’t really replicate across them (Table E.2), all we have is a messy average. For educational attainment, heritability was 0.08, low even by the standards of this method. Then there was this recent paper from the TEDS, which found a much more modest within-family molecular heritability of g at 0.3 but a decent one for education. These molecular methods don’t just fail to replicate pedigree studies: they fail to replicate each other too, other than the fact that they usually find lower heritability than pedigree methods. One reason I’m reluctant to believe them over pedigree studies is that the latter – MZAs, twins, extended pedigrees, adoptees – tended to replicate now-classic findings like h2~0.8, c2~0 for IQ quite well.
An interesting thing I realized in my exchange with Gusev is that he treats within-family molecular genetic heritability estimates (RDR, sib-regression) as exactly analogous to quantitative studies. In a molecular design like sib-regression we exploit very small fluctuations in the actual genetic relatedness of people with the same degree of legal and pedigree-based relatedness. On average, siblings are 50% genetically identical, but because of random processes, some of them end up slightly more or less related genetically. We can not only check if those who are slightly more genetically related end up slightly more phenotypically similar (they do), but we can quantify the importance of, say, 1% of extra genetic relatedness. If we extrapolate this, we can estimate how much extra similarity going from 0% to 100% would cause: the effect of all genes, i.e. heritability.
There are plenty of cases in the hard sciences where these extrapolations work just fine. If you measure how much energy it would take to heat a gas 1 by degree you have a pretty good idea how much it would take to heat it 1000 degrees. I think Gusev has a hard science background so I see how he sees this as just another way to do a quantitative genetic study. But when we get a smaller slope in a design like this than expected from a twin study, can we really discard real-life examples about the similarity of MZAs and the dissimilarity of adoptees, along with all kind of other pedigree studies, and conclude that the substantial similarity of family members is due to the shared environment after all?
I made this chart based on Bingley et al, see also a similar one here. It shows the phenotypic similarity in education (asterisks) of various family members, together with what would be expected from a purely genetic model for simplicity (red lines, expected correlation=male MZ correlation * genetic relatedness). For education, there are clear shared environmental effects, maybe from within-generation effects – siblings and cousins are more similar than expected, although parent-child and avuncular pairs are not – but the effect of genes shines through. Would you have thought that people are more similar to their uncle or his kids if he is an MZ, not a DZ twin of their father?
In this post, I’ll reflect on some other ideas commenters raised and I’ll also present the ideas I think are the best arguments against hardcore hereditarian claims.
Gene-environment correlations
One argument that keeps coming up against hereditarianism is gene-environment correlations: the idea that genes merely index the environment truly causing our traits. I wrote about the passive, reactive, and active forms in my previous piece. For us, the active form is the most interesting: the idea that genes don’t directly code your intelligence or your personality, only what behaviors you are likely to engage in, and your gene-typical behaviors will shape your traits over time. If your behaviors resulted in different experiences, or if these experiences were artificially provided to people who don’t normally seek them out, the effect of genes would be different. Active gene-environment correlations are supposed to explain the Wilson effect and genetic amplification over development. The importance of genes grows as you get older (Wilson effect) and it’s not because new genes enter the game, it’s because the effect of the same genes becomes stronger (amplification) – maybe because the experiences the genes expose you to indirectly accumulates over time.
One way to think about this is that
"it matters not one whit whether the effects of the genes are mediated through the external environment or directly through, say, the ribosomes".
Some genes make us synthesize different proteins, some make us behave differently, both make us different, the distinction is academic, we are seeing gene effects on phenotypes. I never liked this argument very much because the biological and behavioral pathways imply a very different landscape for the potential for interventions. If, for example, IQ genes cause true biological changes then maybe we can design nootropics to make people smarter, but not much else. If, however, some people just inherit the tendency to engage in behaviors that make them smart, then we can phenocopy them, we can make everybody do whatever some genetically predisposed people do naturally, and make everybody smarter.
In his book “Making sense of heritability”, Croatian philosopher Neven Sesardic makes an argument for the biological pathway I rarely see. He describes just how the causal paths between genes and environments would run assuming biological (direct genetic) and behavioral (gene-environment correlation) pathways. Using a typical MZ IQ correlation of 0.75, the numbers could go something like this:
In both cases, we are assuming that genetic variants first cause an endophenotype (something like “bigger brain” or “better axon myelination” or “more efficient serotonin synthesis”, it doesn’t have to be one specific thing). The endophenotype, in turn, either causes IQ directly (biological pathway), or it first makes you engage in a behavior or seek out an environment, which in turn causes IQ (behavioral pathway). In the latter case, we are dealing with active gene-environment correlation: your genes don’t immediately make you smart, but they make you behave in a way that ultimately does. The argument also works for evocative correlations, except your genes don’t make you do something, they invite other people to do the same.
You can immediately see that because there are more steps between the genes and IQ in the behavioral pathway, we need higher effects to still end up with the same IQ correlation at the end of the paths. In both cases, we generously but realistically assume 100% penetrance (a perfect correlation between genotype and endophenotype). In the biological effects case, we have r=0.86 between the endophenotype and IQ (75% heritability), which is high but not crazy, genes can sometimes reliably code phenotypes or evolution would be impossible. However, if we assume gene-environment correlations, not only would the endophenotype need to have a very strong effect (r=0.93) on IQ-increasing behavior, but this IQ-increasing behavior should be incredibly effective at raising IQ!
Just what are some people with the right genetic predisposition doing that makes them smart? Whatever it is, even if we assume a perfect correlation between endophenotype and IQ-increasing behavior, it would need to have an r=0.86 effect on IQ. It cannot be better schooling: curriculum reforms don’t even really improve subject-specific grades in the short term. It cannot be more schooling: going to school longer has at most a minor, non-g-loaded influence on IQ. It cannot be puzzles, brain teasers, being mentally active: these just don’t work after publication bias and placebo effects are accounted for. It must be accessible even outside of a rich first world environment because high IQ heritability was found even in Nigerian and Indian samples (although not a Sudanese one and this paper argues using Russian data that heritability was quite low during the chaotic, highly unequal 90s). If a high-quality environment would be needed to max out your genetic potential, heritability would be universally low in the third world because even people with a high genetic predisposition for intelligence could not engage in the behaviors that actually raise intelligence.
For these reasons, whatever behavior the people genetically so predisposed seek out to make them smart must be something 1) quite different from what families and schools do to make you smart, 2) different from brain teasers or cognitive training because these don’t work, 3) available even in poor countries.
I’m not writing this to totally discount active gene-environment correlations. Maybe it’s many small, frequent, self-paced behaviors that make you smart, and you can’t emulate these by forcing high-intensity interventions on people for a few months. I remember being 6-7 years old in our small town commieblock apartment in early 1990s Hungary. We had an old i386 computer and CDs with demo games I would play with a lot, although we had no money for full games or an audio card. I borrowed and kept an English dictionary by the computer and whenever I encountered a new English word, I would pause the game and look it up. (I had already taught myself how to read in kindergarten.) I would steal literature from my grandparents and when I had a little money, I bought myself a geographical atlas which I spent hours browsing, fantasizing about places like Nauru and Monte Cinto and Monte Rotondo. I clearly had a deeply ingrained, strong natural tendency to teach myself things and I like to believe that this contributed to who I am today, not just biological processes coded by my genes. If I’m correct, it would still be hard to narrow down the specifics of my IQ-increasing behavior because it was so many small things. Even if you could somehow faithfully design the East Hunter Kid Smartening Intervention, most 6–7-year-olds wouldn’t like doing these things as much as I did so they would skimp out, cut corners and do everything half-heartedly and it likely still wouldn’t work. If genes cause trait-changing behaviors this fine, then maybe it is better to treat their effect as just gene expression because we can’t emulate them any easier than a thousand minuscule changes in protein synthesis.
Gene-environment interactions
Another form of gene-environment interplay is a gene-environment interaction (G*E). This means that depending on the environment, the same genes can result in different phenotypes.
In the same book I mentioned above, Neven Sesardic introduces the concept of “common sense” G*E. You can have genius genes, if you get a head injury or some brain-scrambling perinatal infection, you will never be anything but an imbecile. If you grow up in the jungle without books, you will never learn how to read. This is one type of G*E that is definitely real but probably doesn’t do much to undermine hereditarianism.
Sesardic calls the other kind of G*E “biometric”: depending on the level of some environmental variable, the effect of genes differs. Because the “environmental variable” can be anything, the law of large numbers guarantees that some version of this is also true. For example, in the Bingley paper, the environment was being exposed to a school reform: do genes matter more in those exposed to more schooling? (Not really.) Is the heritability of IQ changing over time? Probably not. Education? Maybe decreasing. Do mothers with red hair have a larger shared environmental influence on your personality? OK, I don’t have a study for this one. Because there are infinitely many interactions to be tested, some must be real but we will never be able to reliably tell which ones because the possibility for p-hacking is infinite.
The most serious story about G*E is the Scarr-Rowe hypothesis: genes are more important in the upper social classes because the environments are already maxed out. The Scarr-Rowe hypothesis treats the environment as a source of trouble: if you are poor or your parents are stupid and violent, you have a disadvantage which masks your genes so they matter less and the shared environment more. The best you can hope is to have none of these problems – indicated by a higher social class of origin – so your genetic potential can shine through, evident from higher heritability and lower shared environmental influences. The Scarr-Rowe hypothesis blew up in popularity after one 2003 paper by Eric Turkheimer which found evidence for it. The paper was cited almost 2000 times but it was never really replicated. A meta-analysis published in 2015 found such an effect in the United States, but not outside of it – maybe strong European social nets max out environments even for the poor? But then a very large study – bigger than the meta-analysis – found no Scarr-Rowe effect in America either. Some other studies found some evidence for the Scarr-Rowe hypothesis, some none at all, one of the largest in the UK Biobank even the opposite pattern: lower heritability in the upper social classes. Maybe there is something to the Scarr-Rowe hypothesis, but I’m not sure. Heritability seems mostly independent from social class (and also race).
However, I still think G*E is not only real, but it makes genes the less important force if we zoom out far enough.
Heritability is the proportion of individual differences that arise due to differences in people’s genes. There is a lot to unpack in this sentence. Between MZ twins, every difference is automatically nonshared environmental: no difference in genes, no heritability. If they were real, Star Wars clone troopers probably had somewhat different personalities and intelligence: these are would be all environmental.
In the same way we eliminated genetic differences in these examples to reduce heritability to zero, we can also constrain functionally important environmental differences to zero. This is arguably what happens in a typical twin study, which compares families who may differ in their income levels, education, violence at home and many other traits, but still generally live in the same era in the same country.
It’s kind of a big deal that growing up in a richer, better educated or less violent family is not a “functionally important environmental difference”, as suggested by low shared environmental effects in the quantitative genetic literature. It falsifies much of sociology, psychoanalysis, and popular Marxist style ideas about what causes inequality in society. But just as no heritability of personality in cohorts of clone troopers didn’t mean that genes cannot influence personality, this here also doesn’t imply the environment can’t: it’s just that most of the meaningful environmental differences are not there between families living in the same country in the same era.
It is called the ecological fallacy when we assume that an explanatory mechanism that works on one level also automatically works on another level – for example, that if genes explain most individual differences in a contemporaneous twin/molecular genetic sample, then genes will also explain the same in every context. Yes, between adult males, most height differences are due to having different genes – heritability. But brothers in the same family tend to be taller than their sisters even though heigh-related genes are segregated randomly between siblings: women just end up shorter even with the same genes because increasing estrogen levels during puberty fuse their growth plates early. Within an elementary school, age is the best predictor of height.
A purely genetic explanation also breaks down when we pool different countries and different eras, which is the kind of G*E that I thinks challenges hardcore hereditarianism most effectively.
The most conspicuous example of a gene-environment interaction can be seen for height. (Forget about IQ and the Flynn effect: we are not sure if people actually got smarter in the past century or only better at writing tests, probably the latter. Height is objective.) In typical family studies, height is highly – almost perfectly – heritable. Yet, there has been over a standard deviation of an increase in height in the past century or so: given the same height genes, you ended up much shorter in 1825 than in 2025.
Nobody lives like it’s 1825 anymore so one could argue that these are unimportant environmental differences[1]. But we have a natural experiment about something similar: North vs. South Korea. The Koreans are just one people with no plausible segregation of height genes. Yet, after the artificial division of the country in the 1950s, South Korea ended up a modern capitalist country and North Korea stayed poor and communist. Contemporary South Koreans are over a standard deviation taller than North Koreans.
Mean heights of North and South Korean males. Before you come up with some galaxy brain story about how South Koreans were always taller, look how the height difference disappears in the oldest cohort. A long time ago, all Koreans were poor and short but now only North Koreans are. Within the same country and era, it’s genetics that mainly causes height differences, but big enough differences in the environment can be more important than genes.
If we could jointly analyze extended Korean families, we would likely find that the influence of the shared environment – which side of the border you ended up on – is not only real, even for something like height, but possibly trumps genetics. Given the same genes, it may not do much for your height if you end up in an American family with a better or a worse diet, but North Korea vs. South Korea-level environmental differences are big enough to matter.
Another striking evidence for a gene-environment interaction are the differential income and development levels within Europe. The map of my preferred development indicator, nominal gross wages (no unrealistic oil or financial offshoring effects, no weird PPP deflators, no discrepancy in what counts as “net”) looks like this:
For Lithuania and Romania, so called “super-gross” wages are displayed, which include taxes paid by the employer, not by the employee. Most countries do not include these, so much for my preferred indicator.
In the HBD-sphere, it is generally assumed that international differences in development are due to differences in the genetic potential of populations, mostly captured by IQ scores. I do believe that there is likely a difference in the genetic potential for intelligence (and maybe other traits) of major races, so on a global scale there is much merit to the HBD argument. But within Europe, genetic distances are minimal, migration and intermarriage was frequent, so it is not plausible that genetic differences account for the quite large differences in development. Actually, there is no difference in phenotypic IQ either: Russia, Hungary or Poland scores just as high as England or France. Yet, there are easily twofold or threefold differences in development between genetically highly similar populations (often legally part of the same country just a century or so ago), most notably when comparing Austria and Germany to their Eastern neighbors who were exposed to Communism, and countries that made it in the EU after the fall of Communism to those that did not. For example, up to World War 1, Czechia was just one of many areas in the Habsburg empire, not much more different from Austria than two US states, same laws, same taxes, same architecture, the same or even higher level of development, in many ways the same people – something like a third of the population of contemporary Czechia was ethnically German until World War 2. Yet, after just 40 years of Communism, despite the 30 years that passed since then, average Czech incomes are still less than half of Austria. I’m in the bad company of far-left activist authors when I say that interventions by powerful external actors, “structural forces”, and setbacks in the distant past can sometimes explain important differences today better than genes, but I think there are cases when this is true, and I’m acutely aware of the Eastern European example.
These between-era, between-country differences in environments are a grossly understudied field and likely a strong source of potential environmental effects. This is the drum a good anti-hereditarian should be beating, not arcane issues with genetic modelling methods.
[1] It is also true that height may have been just as heritable 200 years ago as today, the people with the most IQ genes ended up the tallest, it’s just that the absolute value of “tallest” changed. (One could compare the correlation between a height PGS extracted from archeological samples with femur length or skeleton length and compare its accuracy with a modern sample to check if this is true.)
To note, the concepts of biometric gene × environment interaction (G×E) and heritability × environment interactions are frequently conflated in the literature but represent distinct phenomena. G×E, a term in standard biometric models, quantifies the proportion of phenotypic variance due to interactions between genotypes and environments, where specific genotypes exhibit differential responses to environmental conditions. For example, one plant variety may thrive in fertile soil but perform poorly in arid conditions, while another shows the reverse pattern, with this variance attributed to G×E. Conversely, heritability × environment interactions describe how the proportion of phenotypic variance explained by genetic factors (heritability, h²) varies across environments, typically due to changes in total phenotypic variance. For instance, human height may have high heritability (h² = 0.8) in a stable environment, but in a malnutrition-prevalent environment, increased environmental variance may reduce heritability (e.g., h² = 0.5), even if genetic variance remains unchanged. In essence, G×E captures genotype-environment synergies, whereas heritability × environment interactions reflect shifts in the relative genetic contribution to phenotypic variance.
Nice follow up. I often make the same point. A note: I wouldn’t be too quick to dismiss that the Flynn effect taps a real increase. Sure, measurement is a bigger concern than for height. But surely, the fact that we have good evidence that some of the causal antecedents changed over time (nutrient deficiencies, general health, and education) as well counts for something. I think it can be squared with the problem that it cannot be true that people a hundred years ago were disabled if you consider specialization. We probably lost something on a few specific skills around navigation, knowledge of plants and crafts (not tapped well in standard tests) and gained in academics.