Nature
Article
Nature is a recurring publication in the Astral Codex Ten archive, appearing 16 times across 16 issues between March 03, 2021 and August 14, 2025. The archive places it in contexts such as “was reviewed in … Nature”; “a Swedish team published in Nature”; “article in Nature says there is “little evidence”“. It most often appears alongside Science, Twitter, FDA.
Metadata
- Category: Publications
- Mention count: 16
- Issue count: 16
- First seen: March 03, 2021
- Last seen: August 14, 2025
Appears In
- Links For March
- Lockdown Effectiveness: Much More Than You Wanted To Know
- Links For November
- ACX Grants Results
- Contra Hoel On Aristocratic Tutoring
- Your Book Review: Making Nature
- Open Thread 239
- Highlights From The Comments On Supplement Labeling
- Open Thread 255
- Henrietta Lacks Seems Like A Nice Person, But Not A Scientific Hero
- Followup: Quests And Requests
- Links for July 2024
- Missing Heritability: Much More Than You Wanted To Know
- Highlights From The Comments On Missing Heritability
- Your Review: Of Mice, Mechanisms, and Dementia
- In Defense Of The Amyloid Hypothesis
Related Pages
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- Science (5 shared issues)
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- Twitter (5 shared issues)
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- FDA (4 shared issues)
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- Scott (4 shared issues)
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- Bryan Caplan (3 shared issues)
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- Cell (3 shared issues)
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- Congress (3 shared issues)
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- EA (3 shared issues)
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- France (3 shared issues)
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- Harvard (3 shared issues)
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- PLOS ONE (3 shared issues)
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- Sasha Gusev (3 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
26: The Mongol In Our Midst was a 1920s pseudoscience book claiming that Down’s Syndrome (sometimes called mongolism because affected babies look kind of Asian if you’re racist and have a vivid imagination) was literally caused by relic Asian genes that Europeans got from Mongol hordes raping their ancestors. Seems to have been taken somewhat seriously at the time and was reviewed in JAMA and Nature, though I can’t access the reviews to see how critical they were.
Inline links: The Mongol In Our Midst
Probably the most-cited study (1177 times!) on the effect of lockdowns is Flaxman et al from mid-2020. They look at European countries during the first wave of COVID in March 2020, when they instituted various policies, and how that affected virus transmission. They find that nothing except mandatory lockdown (which I think they’re using to mean full shelter-in-place orders) did anything, mandatory lockdown was extremely effective, and that lockdowns saved about three million lives.
Inline links: Flaxman et al
This study has been heavily criticized, I think fairly, with especially good critiques coming from blogger Philippe Lemoine, a Swedish team published in Nature, and a German team in Frontiers In Medicine. They converge on a few points. First, a bug in the model attributes almost all of the transmission reduction in a country to whatever the last intervention was that the country tried. Since most countries started with weaker interventions and then moved on to full lockdown, the model concluded that full lockdown was responsible for almost all the transmission reduction. In the one country that didn't institute lockdown during the period studied, Sweden, there's about the same amount of transmission reduction, but the model attributes all of it to the last thing Sweden tried - a ban on public gatherings - even though in every other country it says such bans had no effect.
Boris Johnson (left) is 5’9, so the guy in the middle must be gigantic. Who is he? Looks like it’s Milo Djukanovic, President of Montenegro, who’s 6’6 (198 cm). Is he the tallest world leader? It seems like he’s tied with his colleague across the border, Serbian president Aleksandar Vucic. Why are Balkan leaders so tall? As usual, the answer is “genetics”. This article says: It has been noted that men from Herzegovina are taller on average than men in other places—the average male height is just over six feet...Putting all the data together, researchers concluded that the most likely cause of larger-than-average height of Herzegovinian men is lifestyle during the Paleolithic—men hunted large animals such as mammoth for survival—such a diet, heavy in protein, combined with small population densities, would have provided ideal conditions for height selection, resulting in increasingly taller men who passed the trait down through their I-M170 chromosome to future generations. Some sources note that they manage to beat the Dutch despite the latter country’s much higher human development index. The Dutch are probably tall through a combination of nature and nurture; Balkan people are tall through nature alone. 7: Eliezer Yudkowsky doesn’t need more ego boosts, but an idea he had a couple of years ago - using strings of bright lights to provide a better and brighter experience for Seasonal Affective Disorder sufferers than regular light boxes - spread from him to the rationalist community to the wider world, and has finally gotten tested in a formal study (see Acknowledgments section). Results seem vaguely positive: "SAD symptoms of both groups improved similarly and considerably...exploratory analyses indicate that a higher illuminance is associated with a larger symptom improvement in the BROAD light therapy group" 8: Percent of people who choose woke options on polls very tentatively and preliminarily seems to be going down post-Trump (h/t Richard Hanania). 9: Twitter conspiracy theories 10: Did you know: all those reconstructions of “how classical art would have looked with the original paint” are probably inaccurate. There is no reason to think the Greeks and Romans used garish technicolor hues on their statues; what evidence we have suggest they were good at shading, and the statues were probably colored very tastefully. 11: Complaints about how Karl Friston uses the term “Markov blanket” 12: Trevor Klee on the claim that cyclosporine patients don’t get dementia. Apparently there was a big study where basically nobody on the immunosuppressant cyclosporine ever got dementia, and there are some theoretical reasons why cyclosporine might prevent neurodegeneration. But another study found people on cyclosporine got dementia at the usual rate. I think in a situation like this you should have a really high prior on “the people who got the crazy result bungled their study somehow”, but I’m interested in hearing what other people think. 13: Also from Trevor: a history of fluvoxamine treatment for COVID. 14: To tide you over until the next book review contest, here is awanderingmind’s review of The Conquest Of Bread. 15: Claims: cnbc.com/2021/11/05/sam…\nft.com/content/dcb75a… (better article, but paywalled)","username":"moskov","name":"Dustin Moskovitz","profile_image_url":"","date":"Fri Nov 05 15:49:46 +0000 2021","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":184,"like_count":1188,"impression_count":0,"expanded_url":{"url":"https://www.ft.com/content/dcb75a56-ca23-439c-96db-56483979bf34","image":"https://bucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com/public/images/80a58c96-c72f-4301-b571-aa9384f132bd_2400x1350.jpeg","title":"Subscribe to read | Financial Times","description":"News, analysis and comment from the Financial Times, the worldʼs leading global business publication","domain":"ft.com"},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> 16: Big trial on Vitamin D for depression finds null result. Peter Attia tries to tear it apart here, but I am unconvinced, especially in the context of Vitamin D never working for any of the things people say it does besides the most boring aspects of bone health. 17: “California is actively considering the adoption of flawed and inequitable guidance on math curricula based on misleading data and inaccurate success metrics reported by San Francisco Unified School District (SFUSD)...Based on our review of the data, we found misleading, unsupported, and cherry-picked assertions of success for the new math program. We noted that overall test scores are down and enrollments in UC-approved advanced math classes have dropped as well.” It looks like San Francisco is trying the good old “lower standards, then when more kids meet the standards, claim your school reform plan worked” trick again. 18: A new study claims that self-reported “Long COVID” symptoms are more associated with believing you’ve had COVID than with actually having it (as measured by serologic testing), which sounds like pretty strong evidence that it’s psychsomatic. Expert reactions are mixed-to-negative, although the only one of these that doesn’t sound like excuse-making is Dr. Rossman’s about the unreliability of the tests. I haven’t confirmed test reliability stats but Philippe Lemoine also thinks this is a plausible confounder. 19: Noahpinion: What If Xi Jinping Just Isn’t That Competent? I appreciated this for making me think, and for underlining the extent of the difference between the Deng/Jiang/Hu era and what Xi’s doing. I especially appreciated this line, which I’d never thought about before: Xi presided over the end of China’s hypergrowth. To some extent this is not his fault. No country can grow at 10% forever, and there were many structural forces pushing downward on China’s numbers — the end of the demographic dividend, the exhaustion of rural surplus labor (the Lewis Turning Point), the saturation of export markets, and so on. But China is also slowing down earlier than South Korea, Taiwan, or Japan did in their day. China’s per capita GDP (at PPP) is still only about 1/3 that of a developed country, so if they stop catching up at about half of developed-country levels, that will not be a great showing. A big lesson of the past twenty years has been “actually liberal democracy isn’t necessary to reach developed-country status”, so it would be quite the twist if it turned out you needed liberal democracy to reach developed-country status. This gets pretty close to the great mystery of why some less-developed countries “catch up” and others don’t; whatever happens in China is going to be a really useful data point. 20: Variations on the fable of The Frog And The Scorpion. 21: You’ve probably heard about the University of Austin, the new project by a bunch of wokeness-critical academics to start a new university that won’t cancel people or force conformity (New York Post article, Politico article - these were the two least “you need to be super-outraged about this right now” articles I could find). Tyler Cowen and Larry Summers are involved; Steven Pinker was supposed to be but left for unclear reasons. My thoughts, in no particular order: Even forgetting the political aspect, attempts to start new universities are always welcome.
Inline links: Milo Djukanovic, Aleksandar Vucic, This article, in a formal study, Richard Hanania, Twitter conspiracy theories, There is no reason to think, Complaints about, cyclosporine patients don’t get dementia, a history of fluvoxamine treatment for COVID, The Conquest Of Bread, Vitamin D for depression, here, is trying, A new study, Expert reactions, Philippe Lemoine also thinks, What If Xi Jinping Just Isn’t That Competent?, Lewis Turning Point, slowing down earlier, per capita GDP (at PPP), the great mystery, Variations on the fable of The Frog And The Scorpion, New York Post article, Politico article
33: I’d previously cited a claim in Joseph Henrich’s Secret Of Our Success that people liked spicy foods because they were antibacterial, but an article in Nature says there is “little evidence” to support that claim.
Inline links: an article in
Stuart Buck, $50,000, to help launch the Good Science Project, “a science policy think tank that will focus on essays, blog posts, videos, and other public advocacy about how to improve science funding in the US.” Buck was VP of Research at Arnold Ventures, helped start the Center for Open Science, and has lectured at DARPA and IARPA and written pieces for Science and Nature. You can read more about his philosophy of science funding here or follow @GoodSciProject for updates.
Inline links: here, @GoodSciProject
There are a bunch of other analyses (really, laments) of a similar nature I could name, from Nature’s “Scientific genius is extinct” to The New Statesman’s “The fall of the intellectual” to The Chronicle of Higher Education’s “Where have all the geniuses gone?” to Wired’s” “The Difficulty of Discovery (Where Have All The Geniuses Gone?)” to philosopher Eric Schwitzgebel’s “Where are all the Fodors?” to my own lamentation on the lack of leading fiction writers.
Inline links: Scientific genius is extinct, The fall of the intellectual, Where have all the geniuses gone?, The Difficulty of Discovery (Where Have All The Geniuses Gone?), Where are all the Fodors?, lamentation on the lack
He argues the most likely cause is the decline of “aristocratic tutoring” - an educational method typical among the ultra-rich of the past - and its replacement with normal public (or private) schools. The answer must lie in education somewhere [...] paradoxically there exists an agreed-upon and specific answer to the single best way to educate children, a way that has clear, obvious, and strong effects. The problem is that this answer is unacceptable. The superior method of education is deeply unfair and privileges those at the very top of the socioeconomic ladder. It’s an answer that was well-known historically, and is also observed by education researchers today: tutoring. […] Let us call [the] past form aristocratic tutoring, to distinguish it from a tutor you meet in a coffeeshop to go over SAT math problems while the clock ticks down. It’s also different than “tiger parenting,” which is specifically focused around the resume padding that’s needed for kids to meet the impossible requirements for high-tier colleges. Aristocratic tutoring was not focused on measurables. Historically, it usually involved a paid adult tutor, who was an expert in the field, spending significant time with a young child or teenager, instructing them but also engaging them in discussions, often in a live-in capacity, fostering both knowledge but also engagement with intellectual subjects and fields. He amply proves that many of the great geniuses of the past, including Bertrand Russell, Albert Einstein, and John von Neumann received tutoring like this, and suggests that its absence (more because of strengthening democratic norms than because people don’t have the money) might be why we don’t see figures of their stature anymore. II. I agree that this kind of tutoring sounds great. I wouldn’t be surprised if it has a big effect size. But it’s not the reason we have fewer geniuses. Why not? Suppose that half of past geniuses were tutored this way, and half weren’t. Even if every single genius who was tutored owed his genius entirely to the tutoring, the tutoring could only explain half of geniuses. That means that after the tutoring stopped, we would expect half as many geniuses. But Hoel is making a stronger claim: that there are almost no geniuses today. For aristocratic tutoring to explain that, we would need for almost all past geniuses to be aristocratically tutored. But as far as I can tell, that isn’t true. Probably well below half of them were. Just to give some examples: Isaac Newton went to a local school at at 12, and to Cambridge at 17. The Wikipedia page on his early life doesn't mention "tutor", except in the context of a college teacher. His adopted father was a country parson, and his family wasn't rich enough to do aristocratic tutoring even if they'd wanted to. Articles on his early life stress his self-motivated nature: he was constantly building things and observing things on his own time. Wolfgang Mozart was tutored, but primarily by his father, himself an excellent violinist. According to his Wikipedia article, "In his early years, Wolfgang's father was his only teacher". Mozart was already an obvious child prodigy by 6 or 7, and wrote his first symphony at 8. I can't find any evidence that non-family members contributed to his education. This kind of tutoring is still common; my wife learned cello from her grandmother, a professional music tutor. Charles Darwin went to a local school at age 8, switched to a boarding school at 9, spent a summer at age 16 following his father (a doctor) around as he treated patients, then went to medical school. He switched to regular college at Cambridge at 19, where he seemed to have a pretty traditional education. Wikipedia has a long article on his education, which doesn't mention the word "tutor" until college age, when he "spent the autumn term at home studying Greek with a tutor". Later in college, he "joined other Cambridge friends on a three-month "reading party" at Barmouth on the coast of Wales to revise their studies with private tutors". I don't think he had a stronger relationship with being tutored himself, especially not in childhood. His summer following his father around learning medicine was probably good for him, but not outside the bounds of what still happens today (I followed my father around learning medicine). Louis Pasteur was born "to a Catholic family of a poor tanner". He went to primary school at 8 and college at 16. I can't find any evidence he was tutored. Charles Dickens barely seems to have been educated at all. His family was so poor that he spent some of his childhood working in a sweatshop. During other periods they did a little better and he went to small lower-to-middle-class private schools. Dickens seems to have gotten most of his education by reading novels on his own. Thomas Edison grew up poor in Michigan. Again according to Wikipedia, "Edison was taught reading, writing, and arithmetic by his mother, who used to be a school teacher. He attended school for only a few months. However, one biographer described him as a very curious child who learned most things by reading on his own. As a child, he became fascinated with technology and spent hours working on experiments at home." Hoel argues that the decline in aristocratic tutoring is “why we stopped making Einsteins”. But then why did we stop making Newtons, Mozarts, Darwins, Pasteurs, Dickenses, and Edisons? III. One other argument: Hoel cites Holden Karnofsky’s Where’s Today’s Beethoven?, which suggests that music is a typical case of the genius decline. But aristocratic tutoring in music is alive and well. When my brother was identified as a piano prodigy, my (well-off but not absurdly rich) parents hired jazz musician Linda Martinez to tutor him. I asked around and this is apparently pretty common in music. In fact, it seems common across a variety of fields, especially those that aren’t taught in school and where success doesn’t make you too rich to need tutoring money (a friend brings up chess as another example). If aristocratic tutoring were a significant factor behind declining genius, we would expect to see a split: fields like science where tutoring is rare would lose their geniuses, whereas fields like music where tutoring is common would be as genius-filled as ever. But people use music as a typical example of a declining-genius field. So that can’t be it. IV. So what’s my explanation? You will not be surprised to hear it’s the maximally boring one, a combination of: Good ideas are getting harder to find. In 300 BC, if you noticed that the water level in your bathtub got higher when you got into it, you were allowed to run through the streets shouting “eureka!” and declare yourself to be a genius. Now you would need some 400 page mathematical proof drawing on the topology of eight-dimensional manifolds in order to get that kind of cred.
The world of scientific publishing is organized as a hierarchy of status, much like the hierarchy of angels in the Abrahamic religions. At the bottom are the non-peer-reviewed blog posts and Twitter threads. Slightly above are the preprint servers like arXiv, and then big peer-reviewed journals like PLOS One. Above those are all the field-specific journals, some with higher reputation than others. And at the top, near the divine presence, are the CNS journals: Cell, Nature, and Science.
For an actual hierarchy of journals based on citation data, see this paper, which puts Nature and Science at the top. Might be worth mentioning that it comes from a journal in the Nature Publishing Group family. Leaving aside Cell, a more specialized biology journal that seems to have gotten into the CNS acronym the same way Netflix got into the FAANG acronym, Nature and Science are very similar. They both publish articles in all scientific fields. They both date from the 19th century. They’re published weekly. They jointly won a fancy prize for services to humanity in 2007. And having your paper in either is one of the best things that can happen to a scientist’s career, thanks to their immense prestige. But how, exactly, did Nature and Science become so prestigious? This is the question I hoped Making Nature: The History of a Scientific Journal, a 2015 book by historian of science Melinda Baldwin, might answer. It focuses on Nature, but much of its lessons can likely be extrapolated to Science considering their similarity. I grew curious about this when I realized that most researchers treat journal prestige as a given. Everyone knows that Nature and Science matter enormously, yet few would be able to say why exactly. But this is important! Prestigious institutions, from universities to media companies to major sports competitions, have a huge impact on the world. It’s useful to understand how they came to be, beyond “being famous for being famous.” One reason this is more difficult than it sounds is that we often settle for superficial answers. Selectivity, for instance, is a common explanation: prestige simply comes from obtaining what is hard to obtain, such as a Harvard degree, an Olympic medal or a Nobel Prize. Nature is indeed highly selective, accepting less than 10% of submitted articles (and the vast majority of papers are not even deemed worthy of a submission to Nature by their authors). Yet harsh selectivity alone cannot explain prestige, or it would be trivial to launch a prestigious journal or university just by setting an artificially low acceptance rate. Another facile explanation is longevity. It’s true that prestigious institutions are often old, and indeed Nature has been around for more than 150 years since its birth in 1869. Science is only slightly younger, having been founded in 1880. But there are many older scientific journals: the oldest one, the Philosophical Transactions of the Royal Society, was created two hundred years before Nature, in 1665. Then there are more recent publications that are prestigious: Cell, for instance, was founded in 1974. The correlation between prestige and longevity is real, but imperfect. It also says nothing of causation: does longevity cause prestige, or does prestige cause longevity? What matters is not the span of time per se, but the specific events that happened — in other words, the history. Making Nature, while not specifically about prestige, gives us exactly that. We’ll first examine the origins of Nature and how it disrupted the publishing landscape of its time (Part I). Then we’ll study the factors that allowed it to build a reputation during its first century of existence (Part II). We’ll end with a focus on the 1970s, when selectivity and prestige suddenly became important to Nature and scientific publishing in general (Part III). I. On the Origins of Nature The story begins with Nature’s founder and first editor, Norman Lockyer. Lockyer had a cushy job as a civil servant in the British government, but dabbled in astronomy in his spare time. In the 19th century, dabbling in astronomy in your spare time could be an intellectually productive hobby: the line between professional and amateur science was blurrier then, and it wasn’t hard to contribute original research even without formal training. During the 1860s, Lockyer published several papers on astronomical observations, the most consequential of which might be the co-discovery and naming of the element helium, from his studies of the sun. His reputation grew among the “men of science” (as scientists called themselves then) of Victorian Britain, and he was soon elected to the Royal Society. But astronomy was an expense, not a source of income. Lockyer routinely supplemented his government job by writing nonspecialist scientific articles and books for a lay audience. Then, one day, he had an idea for a new kind of publication. It would be a weekly periodical to disseminate scientific knowledge to the broader public — but unlike the other periodicals that existed at the time, it would be written by the prominent men of science themselves. It would have a simple, evocative name: Nature. Lockyer summarized the two aims of Nature like this: FIRST, to place before the general public the grand results of Scientific Work and Scientific Discovery, and to urge the claims of Science to a more general recognition in Education and in Daily Life; And, SECONDLY, to aid Scientific men themselves, by giving early information of all advances made in any branch of Natural knowledge throughout the world, and by affording them an opportunity of discussing the various Scientific questions which arise from time to time. In other words (and getting rid of the old-fashioned capitalization of random adjectives and nouns), Nature was meant to do two things: communication from scientists to the public, and communication among scientists. It was an interesting idea. It was also a new one; until then the two aims had been separate. Recall that scientific journals have existed since 1665. During their first two hundred years, they primarily served to record the meetings of learned societies. The Philosophical Transactions of the Royal Society were originally just that: summaries of whatever “philosophical” questions were discussed at the Royal Society. Aside from journals, specialized books were common and were in fact the higher-status way to communicate science in Victorian Britain. Charles Darwin’s On the Origins of Species, published in 1859, is the most famous example. Informal correspondence between scientists was also a major, but private, channel: Darwin wrote more than 15,000 letters in his lifetime, enough to fill 30 volumes. With the exception of some books, none of the above were intended for laypeople. Educated non-scientists (professionals, clergymen, statesmen, etc.) instead got their science news from generalist or literary periodicals such as the Athenaeum magazine. The articles in those publications were not written by specialists, but by journalists and dilettantes. Lockyer’s view, shared with his close supporter Thomas Huxley — a biologist known for defending Darwinian evolution — was that they were riddled with errors and theological overtones. It would be better, they thought, if scientists did the work of communicating their research themselves. It was bold of Lockyer and Huxley to assume that scientists would be interested in doing this communication work. They weren’t. Almost immediately after Nature was founded, its contributors ignored the popularization part (“not a high-status undertaking,” Baldwin’s book says) and focused on the intra-science communication part. They did write summaries and abstracts of their own research, as Lockyer had intended, but they expected that their readers would be other men of science. Within three years, the educated laypeople who were Lockyer’s target audience were complaining that they could no longer understand the contents. Thus the first of Nature’s two aims was met mostly with failure. Fortunately, this was balanced out by unexpected success at the second aim. Scientists did actually enjoy writing for Lockyer’s magazine, in large part because it was published weekly. They found that writing a summary of their own research in Nature was an excellent way to share their results quickly and gain attention from other scientists. Books were slow; Darwin took many years to write and publish On the Origin of Species, for instance. The journals of scientific societies were slow; you had to wait for a meeting to take place and then for the meeting’s “transactions” to be published. Private correspondence was fast, but it wasn’t public. Through publication speed, as well as other factors as we’ll see below, Nature filled a niche in the ecosystem. It was the Twitter of 19th-century British science. Soon enough, this model would be copied, most notably by the journal Science in 1880. According to its first editor, Science was explicitly meant to, “in the United States, take the position which ‘Nature’ so ably occupies in England.” In just a few years, Nature had disrupted scientific publishing and established itself as a useful and unique institution of science, recognized by specialists both in the UK and abroad. First page of the first edition of Nature, 4 November 1869 II. One Hundred Years of Building a Reputation Despite its popularity, Nature didn’t become prestigious overnight. Far from it, in fact. Making Nature often reminds us that the journal spent most of its history as a low-grade publication where anything could be printed quickly, as long as it was factually correct. (This was ensured by basic checks from the editorial team; Nature articles were not consistently peer-reviewed until the 1970s.) As late as the 1960s, a researcher publishing a preliminary report in Nature was expected to follow up with a longer paper “in a more serious journal.” In other words, Nature delivered quick and cheap distribution, not luxury brand approval. This changed about fifty years ago, as we’ll see in Part III. But to understand what happened then, we first need to examine the characteristics of the journal in the roughly 100-year period from its early days until prestige took over, starting with a deeper look into publication speed. Publication Speed John Maddox, editor of Nature in the late 20th century, said that “one of Nature’s greatest early assets was the speed of the Royal Mail.” You could write to Nature, be published within a week, and read the replies to your communication within two weeks. This was state-of-the-art communication tech! Consider how many times publication speed is mentioned throughout the first half of the book (emphasis mine): What made Nature unique was, in large part, its ability to act as a venue for . . . discussions via its correspondence columns and its weekly publication schedule. (p. 8) Many British men of science found that one of the fastest ways to bring a scientific issue or idea to their fellow researchers’ attention was to send a communication to Nature. (p. 39) Unlike the literary periodicals, there was almost no delay between the submission of a piece and its appearance in the journal. (p. 63) A second reason Nature’s speed of publication would have been compelling to men of science is that getting one’s work into print quickly had become an increasingly essential part of establishing priority for a scientific finding or theory. (p. 65) Scientific weeklies [such as Nature] played a unique role in researchers’ publishing strategies at the end of the nineteenth century by offering researchers a forum where short articles could be printed quickly. (p. 105) Both the Proceedings [of the Royal Society of London] and the Philosophical Magazine had significant lag times between submission and publication . . ., which made Nature and its weekly turnaround uniquely valuable for the priority-conscious Rutherford. (p. 109) [Rutherford] sent his most interesting experimental results [to Nature] immediately, both as a way of keeping his colleagues updated on his work and as insurance against being scooped as he had in 1899. (p. 112) These quotes highlight two distinct reasons why speed was important. The first, as I hinted at earlier, was Nature’s role as the аcademic social media of its time. It was simply the best way to have discussions about scientific topics — or science itself — that could, unlike private correspondence, reach a large audience. More on this in the next section. The second reason, as shown by the mentions of physicist Ernest Rutherford, was establishing priority. Today we take for granted that being the first to publish new ideas or results is important, but in the 19th century this was less clear. To bring up Darwin as an example again, he kept his thoughts on evolution private for many years, because he wanted to make sure his argument was sound before he submitted it to the public (although he did eventually sense the urgency of publishing the theory before Alfred Russel Wallace did). But as science became professionalized, “not being scooped” became more and more crucial, and the weekly Nature was a good tool to avoid that. All this talk of speed may surprise anyone who has recently submitted a paper to Nature. In 2016, an analysis revealed that the median time for Nature to review a paper was 150 days, i.e. 5 months, up from 85 days a decade earlier. Nature itself reports, for the year 2020, a median time of 226 days between submission and acceptance. We’re a long way from “less than a week.” Why was there a decrease in publication speed? As we might expect, the reason was Nature’s growing popularity, especially among the international scientific community. At least, that’s what happened the first time there was a slowdown, in the mid-20th century. Early on, Nature was a journal for and by British scientists. But in the first half of the 20th century, science in general and Nature in particular began to involve much more collaboration between researchers across borders. It was a big deal, for instance, when a foreign government banned Nature, as Nazi Germany did in 1938; German researchers had been using it as an important source of scientific news. The ban was furthermore covered in non-British media, such as The New York Times, indicating that the journal was internationally newsworthy. Such an increase in international readership meant more letters and articles sent to the editors, and by the 1950s, there was such a backlog that submissions needed to be held for six months or more. In the 1960s, the new editor John Maddox recognized this as a problem. He began his editorship by clearing the backlog, and even printed the date of submission along with each scientific paper to show everyone how quick Nature was at reviewing articles (“often within a month,” Baldwin’s book says). Clearly, Maddox thought that restoring the speedy reputation of the journal was important. He seems to have succeeded, for a time. As late as 1989, during a controversy around cold fusion, a Wall Street Journal article said that Nature was still fast: it was able to print papers “in as little as three weeks instead of the more usual lead time of six to twelve months for other scientific publications.” Thus, despite a dip in the middle of the century due to its popularity and international reach, speedy publication was still an important characteristic of Nature in the 1970s. A second — and so far permanent — decrease occurred more recently, perhaps as a result of prestige and the competition of near-instantaneous online platforms, but that’s another story. Network Effects As of 2022, scientists argue in public on Twitter, blogs, and other online platforms, like ResearchHub. In the 19th century, Twitter and ResearchHub hadn’t been invented [citation needed]. Fortunately, Nature was there. A network effect occurs when the value of a product comes primarily from the people who use it. If there are two competing telephone systems, the most valuable one is whichever has the most users (or at least the users you want to talk to). If you create an improved Twitter clone, then all its amazing features won’t do much if you don’t somehow manage to capture Twitter’s network of several million people. Likewise, Nature became an interesting journal to read and contribute to because it gained the attention of Britain’s scientific elite as the place to discuss big science questions. This role as a forum was a constant in Nature’s history, as Making Nature shows with several detailed accounts of debates that took place within the journal’s pages. Some examples: Controversies over the age of the Earth in the 1880s.
Inline links: this paper, a fancy prize for services to humanity, https://press.uchicago.edu/ucp/books/book/chicago/M/bo20298849.html, https://substackcdn.com/image/fetch/$s_!oY23!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F99a28e6f-d976-477a-8d14-f47510a23908_200x300.jpeg, https://substackcdn.com/image/fetch/$s_!glJ9!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F873e6e2d-15a6-4b31-954b-f24fcd5e0e23_794x1024.jpeg, more than 15,000 letters, https://en.wikipedia.org/wiki/The_Athenaeum_(British_magazine), took many years, https://substackcdn.com/image/fetch/$s_!GYj8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fa4f03221-7d79-42f6-bf6c-35d90fe3f7e5_1142x1600.jpeg, revealed, reports, ResearchHub
I. On the Origins of Nature The story begins with Nature’s founder and first editor, Norman Lockyer. Lockyer had a cushy job as a civil servant in the British government, but dabbled in astronomy in his spare time. In the 19th century, dabbling in astronomy in your spare time could be an intellectually productive hobby: the line between professional and amateur science was blurrier then, and it wasn’t hard to contribute original research even without formal training. During the 1860s, Lockyer published several papers on astronomical observations, the most consequential of which might be the co-discovery and naming of the element helium, from his studies of the sun. His reputation grew among the “men of science” (as scientists called themselves then) of Victorian Britain, and he was soon elected to the Royal Society. But astronomy was an expense, not a source of income. Lockyer routinely supplemented his government job by writing nonspecialist scientific articles and books for a lay audience. Then, one day, he had an idea for a new kind of publication. It would be a weekly periodical to disseminate scientific knowledge to the broader public — but unlike the other periodicals that existed at the time, it would be written by the prominent men of science themselves. It would have a simple, evocative name: Nature. Lockyer summarized the two aims of Nature like this: FIRST, to place before the general public the grand results of Scientific Work and Scientific Discovery, and to urge the claims of Science to a more general recognition in Education and in Daily Life; And, SECONDLY, to aid Scientific men themselves, by giving early information of all advances made in any branch of Natural knowledge throughout the world, and by affording them an opportunity of discussing the various Scientific questions which arise from time to time. In other words (and getting rid of the old-fashioned capitalization of random adjectives and nouns), Nature was meant to do two things: communication from scientists to the public, and communication among scientists. It was an interesting idea. It was also a new one; until then the two aims had been separate. Recall that scientific journals have existed since 1665. During their first two hundred years, they primarily served to record the meetings of learned societies. The Philosophical Transactions of the Royal Society were originally just that: summaries of whatever “philosophical” questions were discussed at the Royal Society. Aside from journals, specialized books were common and were in fact the higher-status way to communicate science in Victorian Britain. Charles Darwin’s On the Origins of Species, published in 1859, is the most famous example. Informal correspondence between scientists was also a major, but private, channel: Darwin wrote more than 15,000 letters in his lifetime, enough to fill 30 volumes. With the exception of some books, none of the above were intended for laypeople. Educated non-scientists (professionals, clergymen, statesmen, etc.) instead got their science news from generalist or literary periodicals such as the Athenaeum magazine. The articles in those publications were not written by specialists, but by journalists and dilettantes. Lockyer’s view, shared with his close supporter Thomas Huxley — a biologist known for defending Darwinian evolution — was that they were riddled with errors and theological overtones. It would be better, they thought, if scientists did the work of communicating their research themselves. It was bold of Lockyer and Huxley to assume that scientists would be interested in doing this communication work. They weren’t. Almost immediately after Nature was founded, its contributors ignored the popularization part (“not a high-status undertaking,” Baldwin’s book says) and focused on the intra-science communication part. They did write summaries and abstracts of their own research, as Lockyer had intended, but they expected that their readers would be other men of science. Within three years, the educated laypeople who were Lockyer’s target audience were complaining that they could no longer understand the contents. Thus the first of Nature’s two aims was met mostly with failure. Fortunately, this was balanced out by unexpected success at the second aim. Scientists did actually enjoy writing for Lockyer’s magazine, in large part because it was published weekly. They found that writing a summary of their own research in Nature was an excellent way to share their results quickly and gain attention from other scientists. Books were slow; Darwin took many years to write and publish On the Origin of Species, for instance. The journals of scientific societies were slow; you had to wait for a meeting to take place and then for the meeting’s “transactions” to be published. Private correspondence was fast, but it wasn’t public. Through publication speed, as well as other factors as we’ll see below, Nature filled a niche in the ecosystem. It was the Twitter of 19th-century British science. Soon enough, this model would be copied, most notably by the journal Science in 1880. According to its first editor, Science was explicitly meant to, “in the United States, take the position which ‘Nature’ so ably occupies in England.” In just a few years, Nature had disrupted scientific publishing and established itself as a useful and unique institution of science, recognized by specialists both in the UK and abroad. First page of the first edition of Nature, 4 November 1869 II. One Hundred Years of Building a Reputation Despite its popularity, Nature didn’t become prestigious overnight. Far from it, in fact. Making Nature often reminds us that the journal spent most of its history as a low-grade publication where anything could be printed quickly, as long as it was factually correct. (This was ensured by basic checks from the editorial team; Nature articles were not consistently peer-reviewed until the 1970s.) As late as the 1960s, a researcher publishing a preliminary report in Nature was expected to follow up with a longer paper “in a more serious journal.” In other words, Nature delivered quick and cheap distribution, not luxury brand approval. This changed about fifty years ago, as we’ll see in Part III. But to understand what happened then, we first need to examine the characteristics of the journal in the roughly 100-year period from its early days until prestige took over, starting with a deeper look into publication speed. Publication Speed John Maddox, editor of Nature in the late 20th century, said that “one of Nature’s greatest early assets was the speed of the Royal Mail.” You could write to Nature, be published within a week, and read the replies to your communication within two weeks. This was state-of-the-art communication tech! Consider how many times publication speed is mentioned throughout the first half of the book (emphasis mine): What made Nature unique was, in large part, its ability to act as a venue for . . . discussions via its correspondence columns and its weekly publication schedule. (p. 8) Many British men of science found that one of the fastest ways to bring a scientific issue or idea to their fellow researchers’ attention was to send a communication to Nature. (p. 39) Unlike the literary periodicals, there was almost no delay between the submission of a piece and its appearance in the journal. (p. 63) A second reason Nature’s speed of publication would have been compelling to men of science is that getting one’s work into print quickly had become an increasingly essential part of establishing priority for a scientific finding or theory. (p. 65) Scientific weeklies [such as Nature] played a unique role in researchers’ publishing strategies at the end of the nineteenth century by offering researchers a forum where short articles could be printed quickly. (p. 105) Both the Proceedings [of the Royal Society of London] and the Philosophical Magazine had significant lag times between submission and publication . . ., which made Nature and its weekly turnaround uniquely valuable for the priority-conscious Rutherford. (p. 109) [Rutherford] sent his most interesting experimental results [to Nature] immediately, both as a way of keeping his colleagues updated on his work and as insurance against being scooped as he had in 1899. (p. 112) These quotes highlight two distinct reasons why speed was important. The first, as I hinted at earlier, was Nature’s role as the аcademic social media of its time. It was simply the best way to have discussions about scientific topics — or science itself — that could, unlike private correspondence, reach a large audience. More on this in the next section. The second reason, as shown by the mentions of physicist Ernest Rutherford, was establishing priority. Today we take for granted that being the first to publish new ideas or results is important, but in the 19th century this was less clear. To bring up Darwin as an example again, he kept his thoughts on evolution private for many years, because he wanted to make sure his argument was sound before he submitted it to the public (although he did eventually sense the urgency of publishing the theory before Alfred Russel Wallace did). But as science became professionalized, “not being scooped” became more and more crucial, and the weekly Nature was a good tool to avoid that. All this talk of speed may surprise anyone who has recently submitted a paper to Nature. In 2016, an analysis revealed that the median time for Nature to review a paper was 150 days, i.e. 5 months, up from 85 days a decade earlier. Nature itself reports, for the year 2020, a median time of 226 days between submission and acceptance. We’re a long way from “less than a week.” Why was there a decrease in publication speed? As we might expect, the reason was Nature’s growing popularity, especially among the international scientific community. At least, that’s what happened the first time there was a slowdown, in the mid-20th century. Early on, Nature was a journal for and by British scientists. But in the first half of the 20th century, science in general and Nature in particular began to involve much more collaboration between researchers across borders. It was a big deal, for instance, when a foreign government banned Nature, as Nazi Germany did in 1938; German researchers had been using it as an important source of scientific news. The ban was furthermore covered in non-British media, such as The New York Times, indicating that the journal was internationally newsworthy. Such an increase in international readership meant more letters and articles sent to the editors, and by the 1950s, there was such a backlog that submissions needed to be held for six months or more. In the 1960s, the new editor John Maddox recognized this as a problem. He began his editorship by clearing the backlog, and even printed the date of submission along with each scientific paper to show everyone how quick Nature was at reviewing articles (“often within a month,” Baldwin’s book says). Clearly, Maddox thought that restoring the speedy reputation of the journal was important. He seems to have succeeded, for a time. As late as 1989, during a controversy around cold fusion, a Wall Street Journal article said that Nature was still fast: it was able to print papers “in as little as three weeks instead of the more usual lead time of six to twelve months for other scientific publications.” Thus, despite a dip in the middle of the century due to its popularity and international reach, speedy publication was still an important characteristic of Nature in the 1970s. A second — and so far permanent — decrease occurred more recently, perhaps as a result of prestige and the competition of near-instantaneous online platforms, but that’s another story. Network Effects As of 2022, scientists argue in public on Twitter, blogs, and other online platforms, like ResearchHub. In the 19th century, Twitter and ResearchHub hadn’t been invented [citation needed]. Fortunately, Nature was there. A network effect occurs when the value of a product comes primarily from the people who use it. If there are two competing telephone systems, the most valuable one is whichever has the most users (or at least the users you want to talk to). If you create an improved Twitter clone, then all its amazing features won’t do much if you don’t somehow manage to capture Twitter’s network of several million people. Likewise, Nature became an interesting journal to read and contribute to because it gained the attention of Britain’s scientific elite as the place to discuss big science questions. This role as a forum was a constant in Nature’s history, as Making Nature shows with several detailed accounts of debates that took place within the journal’s pages. Some examples: Controversies over the age of the Earth in the 1880s.
Inline links: https://substackcdn.com/image/fetch/$s_!glJ9!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F873e6e2d-15a6-4b31-954b-f24fcd5e0e23_794x1024.jpeg, more than 15,000 letters, https://en.wikipedia.org/wiki/The_Athenaeum_(British_magazine), took many years, https://substackcdn.com/image/fetch/$s_!GYj8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fa4f03221-7d79-42f6-bf6c-35d90fe3f7e5_1142x1600.jpeg, revealed, reports, ResearchHub
Making Nature (history of the scientific journal Nature)
Inline links: Making Nature
Our research has also been the basis for important public investigations cited in Nature, NYTimes ('14, '21), Last Week Tonight, The Guardian, etc.
We launched a new project (which received an ACX Grant) to help improve the replication crisis in psychology: Transparent Replications by Clearer Thinking! We're aiming to vastly increase the probability of studies in top journals being replicated in order to change researcher incentives. As soon as new psychology and behavior papers come out in Nature and Science (the two most prestigious general science journals), our plan is to replicate a study from nearly every one of them. Additionally, we'll be replicating randomly selected studies from PNAS, JPSP, and PSci shortly after they are released. You can check out our first three replications now!
It would be an understatement to say that has since been corrected. There have been hundreds of articles talking about how racist and disgusting science is for not treating Lacks’ family better or acknowledging Henrietta the person - see for example this article in Nature saying that Science Must Right A Historical Wrong by various things including “celebrating her life and legacy”:
Inline links: Science Must Right A Historical Wrong
“I want scientists to acknowledge that HeLa cells came from an African American woman who was flesh and blood, who had a family and who had a story,” her granddaughter Jeri Lacks-Whye told Nature.
https://www.nature.com/articles/s41588-022-01016-z
Inline links: https://www.nature.com/articles/s41588-022-01016-z
how does a legislator decide what's a constitutional gun law, when experts disagree? https://tristanroberts.org/news/a-law-without-the-governors-signature
14: Arc Institute (Patrick Collison et al’s biotech research lab) claims to have discovered a gene editing method which is safer and more precise than CRISPR (Nature paper, Twitter discussion).
Inline links: Nature, Twitter discussion
For example, educational attainment is 50% uncorrelated with direct genetic effects. You need to square this to figure out what percent is causal; when you do that, you find that the polygenic score that explained 14% of EA is only 4%pp direct genes, with the other 10%pp being nondirect5 confounders. So yes, it seems like most polygenic scores that don’t validate within families are confounded. However unhappy we previously were that we had only found 14% of genes for EA (vs. 40% expected), we should now be much more unhappy - we really only know 4% of genes that directly cause EA. On the other hand, you might say - so before we only knew 14%pp out of 40%. Now we only know 4%pp out of 40%. This is discouraging, but it doesn’t fundamentally change what we know about nature vs. nurture. Both 4%pp and 14%pp are less than 40% - with either number, we must be missing something or doing something wrong. Probably that’s insufficient sample size. We’ll keep working on sample size and other things, and eventually scrounge up the missing 26%pp or 36%pp or whatever of the variance, so this doesn’t change anything. All it means is that one predictive method that the average person never knew about in the first place doesn’t work as well as we thought. Who cares? Not doctors. So far this research has only just barely begun to reach the clinic. But also, all doctors want to do is predict things (like heart attack risk). They don’t care if they use causal vs. nondirect genes. It doesn’t matter if you’re “only” at higher risk of heart attack because you’re black, or Norman, or because your parents read books to you - you still need more heart attack medication! Polygenic embryo selection companies should care. They offer polygenic scores that can be used to select healthier or smarter embryos. If the predictors they use rely partly on variants that aren’t causal within families, their real benefits could be far lower than advertised. I talked to one of these companies, who said they’d already adjusted for these effects and expected their competitors had too - the proper antidote to this problem, sibling controls, is a natural choice when you’re literally picking between siblings. The biggest losers are the epidemiologists. They had started using polygenic predictors as a novel randomization method; suppose, for example, you wanted to study whether smoking causes Alzheimers. If you just checked how many smokers vs. nonsmokers got Alzheimers, your result would be vulnerable to bias; maybe poor people smoke more and get more Alzheimers. But (they hoped) you might be able to check whether people with the genes for smoking get more Alzheimers. Poverty can’t make you have more or fewer genes! This was a neat idea, but if the polygenic predictors are wrong about which genes cause smoking and what effect size they have, then the less careful among these results will need to be re-examined. But the reason I spent so much time on the subject here is that this has confused a lot of people into thinking heritability itself was confounded and is actually just 4%. When I read my first few blog posts on these findings, I came away thinking they were claiming to have discredited twin studies and heritability. And although I take partial ownership of my own poor reading comprehension, I maintain that the way that the new anti-hereditarians discuss this is pretty bad. For example, Turkheimer’s treatment of the Tan study above is called Is Tan Et Al The End Of Social Science Genomics?, and includes passages like: The median [direct genomic effect] heritability for behavioral phenotypes is .048. Let that sink in for a second. How different would the modern history of behavior genetics be if back in the 80s one study after another had shown that the heritability of behavior was around .05? When Arthur Jensen wrote about IQ, he usually used a figure of .8 for the heritability of intelligence. I know that the relationship between twin heritabilities and SNP heritabilities is complicated, and in fact the DGE heritability of ability is one of the higher ones, at .2336. But still, it seems to me that the appropriate conclusion from these results is that among people who don’t have an identical twin, genomic information is a statistically non-zero but all in all relatively minor contributor to behavioral differences. And comments included things like: I don’t know if [this study] is the end of social science genomics, but it should certainly be the end of attributing significant genetic influence to behavioral traits (despite the recent scientist-generated cartoons touting genes for “income”). And: There's no doubt that this reported findings have dealt a fatal blow to my conviction that behavioral traits are pre-eminently heritable…This is a remarkable example of an objective statistical fact mercilessly crushing the more subjective experiential sense of "A looks and acts more like B than C because A and B have the same parents." This subjective evidence is almost unshakable and universal in its application as a tried and tested psychosocial heuristic. And yet, here we are. Turkheimer is either misstating the relationship between polygenic scores and narrow-sense heritability, or at least egging on some very confused people who are doing that, and the dynamic was bad enough that I got confused myself for a while. But even more confusing, the new anti-hereditarians actually are saying that lots of behavioral traits have very low heritability! But this point requires different arguments, only tangentially related to these. So let’s move on to… Is Heritability Genuinely Low? (Part 1: GWAS & GREML) In the mid 2010s, when genome-wide association studies (GWAS) based polygenic predictors were getting better every year, it was easy to hope they might reach 40% and close the “missing heritability”. But since then, progress has stalled. The second-to-last tripling of sample size, from 300K to 1M between 2016 - 2018, increased predictive power from 6% → 12%. The last tripling, from 1M to 3M between 2018 - 2022, only increased predictive power from 12% → 14%. If you graph sample size vs. predictive power, it looks like there's an asymptote between 15 - 20% or so. (of which - remember - only 5% is directly causal!) Worse, a mid-2010s technique called GREML allowed researchers to estimate the percent of variance in a trait that comes from the sorts of common genes studied in GWAS, without having to identify the genes involved. A 2016 GREML paper suggested that the maximum share of variance that GWASs of educational attainment could ever discover was about 21% (again, compared to 40% predicted genetic from twin studies). Since unavoidable methodological issues will prevent GWASs from reaching the literal maximum possible, this agrees with the evidence suggesting an asymptote between 15 - 20%. So either twin studies are wrong and traits are less heritable than believed, or the heritability must lie somewhere other than the common genes identifiable by GWAS. What about rare genes? GWASs focus on genetic variation common enough to be worth including in a basic genetic test. Most of this is single nucleotide polymorphisms (“SNPs”). A single nucleotide is one letter of DNA - for example, a C or a G. Polymorphisms are genes that commonly vary in humans - sometimes across races (for example, some humans have a gene for light skin, and other humans have a gene for dark skin), and other times within races (for example, some white people have a gene that makes cilantro taste like soap, and others don’t). So SNPs are single-letter spots in DNA where different people often have different letters. How often? Some people say 1%, but the more practical definition is “often enough that someone has noticed and added it to the test panel”. There are three billion letters in the genome, of which only a few million are commonly-tested SNPs. But these SNP studies have limited7 ability to measure personal mutations and rare variants. Sometimes your parents’ egg and sperm cells mess up copying a nucleotide of DNA, and you get a mutation that isn’t inherited from your ethnic group or even from your subgroup/family line - it’s just some idiosyncratic DNA change that you might be the first person in history to have. Since scientists have never seen this mutation before, they don’t know about it and can’t test for it without doing something more expensive than a simple SNP screen. And SNP studies have limited ability to detect anything more complicated than a single letter changing to another single letter. But some mutations are more complicated structural variants. For example, some bits of DNA get stuck on repeat - one person might have GATGAT, another person might have GATGATGATGAT, and a third person might have fifty GATs in a row. Other bits come out backwards. Sometimes a whole chunk of DNA goes missing, or moves to the wrong place. Occasionally a gene reads The Selfish Gene by Richard Dawkins, takes it too seriously, and evolves some ridiculous trick for spamming itself all over the genome. So if even the best molecular studies seem to be asymptoting around 15-20% of variance in educational attainment, but twin studies suggest it’s 40% genetic, might rare variants and structural variants make up the missing 20-25%pp? This remains a topic of bitter disagreement. On the one side, hereditarians bring up a Darwinian argument: imagine a genetic engineer who hopes to find the genes for educational attainment and edit them to make everyone smart and successful. She looks harder and harder, becoming more and more exasperated as they fail to materialize. Finally, she realizes she’s been scooped: evolution has been working on the same project, and has a 100,000 year head start. In the context of intense, recent selection for intelligence, we should expect evolution to have already found (and eliminated) the most straightforward, easy-to-find genes for low intelligence. Therefore, everything left should be convoluted or hidden or impossible to work with. So although this requires a sort of god-of-the-gaps argument - where we keep pushing heritability into whatever genes are too weird for existing techniques to detect - there are some reasons to think God really is in the gaps here. And a 2017 paper uses some clever techniques to estimate the share of intelligence variation lurking in hard-to-measure genes and finds it’s more than half: “By capturing these additional genetic effects, our models closely approximate the heritability estimates from twin studies for intelligence and education.” (see also Wainschtein 2022, Sidorenko 2024) The anti-hereditarians disagree. They cite papers like Zeng which measure the strength of selection on intelligence and suggest that it’s too weak to concentrate so much of the variation in rare genes8. And Sasha Gusev mentions Weiner 2023, which finds that in fact rare variants “explain 1.3% (SE = 0.03%) of phenotypic variance on average – much less than common variants” (other experts say that burden heritability only captures some rare variants and is not the right tool for this problem). But it may not even matter, because another set of findings suggests that heritability is genuinely low even when the rare variants are counted. Is Heritability Genuinely Low? (Part 2: Sib-Regression and RDR) Two newer methods, Sib-Regression and RDR, ask: using what we know from genetic studies, how much genetic variation do we think exists, total, across both common and rare genes? On average siblings share 50% of genes. But there’s a little randomness in meiosis, so some siblings might share 40% and others might share 60%. The more genetic influence on a trait, the more similar sibling pairs who share 60% of their genes will be, compared to sibling pairs who only share 40% of their genes. Since 60%-gene siblings and 40%-gene siblings are both equally part of the same family, you can use these numbers to calculate heritability unconfounded by a range of family factors. This is Sib-Regression. If you do a more complicated statistical process to extend the same idea to relatives other than siblings, it’s relatedness disequilibrium regression or RDR. GWAS asks: Looking at common easy-to-study genes, how much variation in a trait have we explained right now? GREML asks: looking at common easy-to-study genes, how much variation could we ever explain? But sib-regression and RDR ask a question more like twin studies: considering all genes, whether common / rare / easy-to-study / hard-to-study, how much variation is there total? This could address the rare variant objection mentioned above. And in many ways, these techniques are better than twin studies - Sib-Regression eliminates many potential biases, and RDR eliminates even more (although it’s harder to pull off, requiring more genetic information and computational resources). These techniques are new and hard-to-use, and only a few published studies have applied them to the sorts of behavioral traits we’re interested in: Young et al (2018) did Sib-Regression and RDR to genetic data from Iceland. Sib-regression found educational attainment = 40% (±15%) heritable, and RDR found 17% (±9%) heritable. Kemper et al (2021) did Sib-Regression only to genetic data from Britain. It found educational attainment = 14% heritable. This number conflicts with the 40% from the Young paper. Why? Unclear, but it could be selection bias - Young’s Icelandic sample was representative of the country; Kemper’s British population were Biobank volunteers who tend tend to be healthier and higher-class than the population at large. Upper-class people may have restricted range in educational attainment, or different factors affecting their educational attainment compared to the overall population. Either way, these are closer to the low estimates from GWAS and GREML (7% direct, 20% total), than to the higher estimates from twin studies (40%, generally presumed direct). And we can no longer use contributions from rare variants to paper over the difference. So what is going on? It seems like we have to accept one of three possibilities: Either something is wrong with twin studies. Or something is wrong with Sib-Regression and RDR (and then we can explain away GWAS and GREML by saying they’re missing rare variants). Or something is wrong with how we’re thinking about this topic and comparing things. What’s Going On? (Part 1: Is Something Wrong With Twin Studies?) Twin studies have dominated discussion of behavioral genetics for decades, so there’s a vast literature investigating their various assumptions and whether something might be wrong with them. Here are some of the assumptions and what the research says about each. Some of these will be duplicates of the GWAS confounders above, but we’ll go through them again anyway to review how they apply to twins. 1: Parents Treat Fraternal And Identical Twins The Same: Twin studies claim that twins are a uniquely powerful genetic laboratory; both fraternal and identical twin pairs have equally concordant environments, but identical twins have more concordant genes. Therefore, the more similar identical twin pairs are relative to fraternal twin pairs, the more heritable a trait must be. But this conclusion falls apart if identical twin pairs actually have more similar environments than fraternal twin pairs do, maybe because parents (knowing their twins are identical) treat them more similarly than they would fraternal twins. Would-be twin-study-discreditors have been trying to argue that this must be true for decades, but it’s always been a kind of quixotic battle. Remember, twin studies find many behavioral traits like IQ are >60% heritable, so you would need to prove not only that parents treat identical twin pairs differently from fraternal, but that this was an overwhelming effect. Parents of identical twins would have to obsessively expose them to the exact same stimuli in the exact same order; parents of fraternal twins would have to send one to the Gifted Advanced Placement Acceleration program while locking the other in a box and force-feeding them lead pellets. Common sense tells us there are no such differences, and studies confirm this: when parents are wrong about their twins’ status (eg they have fraternal twins, but falsely think they’re identical, or vice versa) their trait similarity matches their real status, rather than the incorrect status that determined how their parents treat them; parental treatment explains less than 1% of why identical twin pairs are more concordant (2, 3, 4). See also Felson 2013, which tries to measure environmental similarity and adjust for it, with minimal effects. Are these two cuties monozygotic or dizygotic? Are you sure? (answer) 2: Fraternal And Identical Twins Have Equally Concordant Uterine Environments: Fraternal twins have different sacs in the uterus and use different placentas. Most identical twins share a placenta, and some share an amniotic sac. If trait similarity is caused by sharing a placenta or sac (maybe because the placenta is defective, the fetal brain is starved of nutrients, and so the person has a lower IQ when they grow up), twin studies would falsely read this identical-fraternal difference as genetic. Luckily this is easy to study; not all identical twins share a placenta or sac, so you can cleanly separate the effect of uterine environment from genetics. If you measure enough traits, you can find small deviations in some, but it’s not clear whether this is just multiple testing, and in any case the deviations are small. The best studies suggest this chips off somewhere between 0 - 3% from heritability estimates9. 3: There is little assortative mating: We discussed this one above in the earlier section on GWAS - smart/pretty/kind/whatever people tend to marry other smart/pretty/kind/whatever people. Why would this bias twin study results? Identical twins share 100% of their genes. Fraternal twins ought to share 50% of their genes - but they get half their genes from their mother, and half from their father. In the degenerate case where the mother and father have exactly the same genes (“would you have sex with your clone?”) even fraternal twins will be extremely similar (although not quite identical, since they’ll get different alleles from each clone). In the more plausible case where mothers and fathers are just a little more alike than chance (eg because smart people tend to marry other smart people), fraternal twins will share a genetic tendency towards a trait somewhat more than their 50% shared genes suggest. Since this makes fraternal twin pairs more (genetically) like identical twin pairs, and twin studies assess heritability as the difference in fraternal-identical-twin-pair concordance, this bias would make twin studies underestimate heritability. But this is the opposite of what you would need to “discredit” twin studies - if this bias is true, then everything is more genetic than twin studies think. And unlike the previous two biases, this one seems real and important, so much so that when you adjust for it, the heritability of educational attainment rises from ~40% to ~50%. I’m only mentioning this one here because some anti-hereditarians argue that you can’t trust twin studies because of assortative mating, without mentioning that this can only bias them down. 4: Population stratification: This is often large and worth worrying about, but it applies to identical and fraternal twin pairs equally, and doesn’t bias twin study heritability estimates much (though it might shift the balance between shared and non-shared environment). See eg the sentence around footnote 30 here. 5: Non-additive / “interaction” effects: These are theoretically interesting, but all research thus far has found they are minimal (1, 2). Some experts think this may miss rarer or harder-to-find interactions; we’ll return to this later. 6: “Genetic nurture”, parent-to-child Mentioned above: if there is a gene for reading books to kids, and reading books raises IQ, it will look like a “gene for IQ”. This isn’t as relevant to twin study estimates of heritability, since both identical twins and fraternal twins are equally related to their parents, and any trait caused by genetic nurture wouldn’t differ between them (and therefore would not falsely appear heritable in this design). Rather, they would appear as shared environment. 7: “Genetic nurture”, sibling-to-sibling That is, suppose your sibling’s traits influence your own development. For example, suppose your sibling has a gene that makes them sabotage your schoolwork, causing you to fail and drop out of school early. An identical twin would share this gene with their sibling more often than a fraternal twin, making it look like a “gene for doing badly at school” (since the people who have it do worse at school than those who don’t). Why are we even talking about this? Do we really think it’s a big part of the variance in behavioral traits? Challenging twin study heritability estimates through this route requires inhabiting a weird no-man’s-land where otherwise-invisible genetic and environmental pathways suddenly flare up when you say the magic words “it was done by a sibling”. For example, this requires a strong effect of shared environment - that is, your educational attainment has to depend on whether you’re being sabotaged or not. But in general, shared environmental effects are weak. And it requires a strong effect of genes - that is, this mechanism only works if your sibling’s tendency to sabotage you is highly genetically determined. But we’re deploying this claim to deny that traits like IQ or educational attainment are highly genetically determined. So to get much out of this, the tendency to sabotage siblings would have to be more genetic than other behavioral traits! The reason this convoluted possibility gets brought up so often is that, unlike the more plausible parent-to-child genetic nurture, twin studies can’t rule it out. So if you really want to deny twin studies, this is one of your best bets. But when investigated, this has effects indistinguishable from zero. I’ve been a bit mean in this whole section, because people really like to dismiss twin studies as “Oh, don’t you know, those depend on assumptions, I bet you never considered that assumptions might be wrong”, and then Gish Gallop you with different assumptions until you give up. But scientists have actually done a lot of really good work checking the assumptions and they mostly hold. An alternative way of validating twin studies (brought up by Noah Carl in this article) is to check them against their close cousins, adoption studies and pedigree studies. Pedigree studies investigate large family trees, and check how trait similarity decreases with genetic distance. They avoid twin specific biases (like different treatment of fraternal vs. identical twin pairs, or different prenatal environments), while adding others like assortative mating. Here are the heritabilities of IQ and EA found in pedigree studies10 (see footnote for sources and caveats, and see also here and here for somewhat similar designs): Adoption studies investigate whether adoptees’ traits are more correlated with their adoptive or biological parents. They avoid a large swathe of biases, at the risk of introducing new adoption-related biases of their own (like the possibility that agencies deliberately place adoptive children with parents who are culturally or behaviorally similar, or the possibility that adoptees were adopted late enough to still get some shared environment from their biological parents). Here are the findings of some of the largest and best11: Both straightforwardly confirmed the larger heritability numbers found in twin studies. I would add the evidence from some less formal “adoption studies”12. During residency, I spent a few months working in a child psychiatric hospital for the worst of the worst - kids who committed murder or rape or something before age 18. Many of these children had similar stories: they were taken from their parents just after birth because the parents were criminals/drug addicts/in jail/abusing them. Then they were adopted out to some extremely nice Christian family whose church told them that God wanted them to help poor little children in need. Then they promptly proceeded to commit crime / get addicted to drugs / go to jail / abuse people, all while those families’ biological children were goody-goodies who never got so much as a school detention. When I met with the families, they would always be surprised that things had gone so badly, insisting that they’d raised them exactly like their own son/daughter and taught them good Christian morals. I had to resist the urge to shove a pile of twin studies in their face. This has left me convinced that behavioral traits are highly heritable to a level that it would be hard for any study to contradict. Ultimate source here. Although the study is confusing about this, I think it’s trying to say that almost 90% of subjects were adopted before age 2. But I don’t think studies do contradict this. Given the degree to which their assumptions have been validated, and the level of confirmation from pedigree and adoption studies, I think they have earned a presumption of accuracy. Doubting the twin studies doesn’t seem like a promising route to reconciling the twin-vs-Sib-Regression/RDR discrepancy. What’s Going On? (Part 2: Is Something Wrong With Sib-Regression And RDR?) Sib-Regression is a clever way of avoiding most biases. Its independent variable - the degree to which some sibling pairs end up with slightly more shared genes than others - is even more random and exogenous than the difference between fraternal and identical twins. It can sometimes have biases related to assortative mating (which would falsely push heritability down), but otherwise it’s pretty good. RDR has many of the same advantages, and allows more diverse relationships and so larger sample sizes. It’s hard to think of ways these methods could be wildly off. There is one caveat: although RDR includes most of the rare and structural variants missed by GWAS, in theory it can miss certain ultra-rare variants which are so uncommon that they aren’t shared between some of the relative pairs used in RDR. De novo variants that occurred during the subject’s own conception would be in this category, if the subject didn’t have children or didn’t pass on that gene13. This seems like a pretty small subcategory of genetic variation, and I wouldn’t normally expect that much of importance to be hiding here, but maybe it’s more important than it seems. RDR also doesn’t include much variance caused by statistical interactions between genes. Although we said above that these are usually found to be insignificant, they might be more important in a trait like intelligence that has been under recent evolutionary selection that lops off easily-detectable sources of variance and leaves only the weird obscure ones behind. There’s limited ability for classical Mendelian dominance to affect common variants, but more complicated genetic interactions might still prove important. Overall these are strong methods, and their failure to converge is troubling. If forced to explain them away, we might tell a story like: So far, there is only one RDR study and a few Sib-Regression studies, so we should wait for more data before updating too hard.
Inline links: 5, Polygenic embryo selection, need, Is Tan Et Al The End Of Social Science Genomics?, 6, like, And, 300K, 1M, 3M, A 2016 GREML paper, 7, evolves some ridiculous trick, a Darwinian argument, a 2017 paper, Wainschtein 2022, Sidorenko 2024, Zeng, 8, Weiner 2023, other experts say, meiosis, Young et al (2018), Kemper et al (2021), their trait similarity, matches their real status, 2, 3, 4, Felson 2013, https://substackcdn.com/image/fetch/$s_!r3kV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd575f2d6-3619-40e6-9a5e-f9f1ec1399a5_650x422.png, answer, The best studies, 9, seems real and important, here, 1, 2, when investigated, in this article, 10, here, here, https://substackcdn.com/image/fetch/$s_!b3LF!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc094f9c0-4c71-48cf-89dc-615498d94812_483x51.png, 11, https://substackcdn.com/image/fetch/$s_!XFWU!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F85f433e5-d141-47b7-8dc5-2271925032e9_483x102.png, 12, https://x.com/cremieuxrecueil/status/1935731422205010135, here, 13
Are these two cuties monozygotic or dizygotic? Are you sure? (answer) 2: Fraternal And Identical Twins Have Equally Concordant Uterine Environments: Fraternal twins have different sacs in the uterus and use different placentas. Most identical twins share a placenta, and some share an amniotic sac. If trait similarity is caused by sharing a placenta or sac (maybe because the placenta is defective, the fetal brain is starved of nutrients, and so the person has a lower IQ when they grow up), twin studies would falsely read this identical-fraternal difference as genetic. Luckily this is easy to study; not all identical twins share a placenta or sac, so you can cleanly separate the effect of uterine environment from genetics. If you measure enough traits, you can find small deviations in some, but it’s not clear whether this is just multiple testing, and in any case the deviations are small. The best studies suggest this chips off somewhere between 0 - 3% from heritability estimates9. 3: There is little assortative mating: We discussed this one above in the earlier section on GWAS - smart/pretty/kind/whatever people tend to marry other smart/pretty/kind/whatever people. Why would this bias twin study results? Identical twins share 100% of their genes. Fraternal twins ought to share 50% of their genes - but they get half their genes from their mother, and half from their father. In the degenerate case where the mother and father have exactly the same genes (“would you have sex with your clone?”) even fraternal twins will be extremely similar (although not quite identical, since they’ll get different alleles from each clone). In the more plausible case where mothers and fathers are just a little more alike than chance (eg because smart people tend to marry other smart people), fraternal twins will share a genetic tendency towards a trait somewhat more than their 50% shared genes suggest. Since this makes fraternal twin pairs more (genetically) like identical twin pairs, and twin studies assess heritability as the difference in fraternal-identical-twin-pair concordance, this bias would make twin studies underestimate heritability. But this is the opposite of what you would need to “discredit” twin studies - if this bias is true, then everything is more genetic than twin studies think. And unlike the previous two biases, this one seems real and important, so much so that when you adjust for it, the heritability of educational attainment rises from ~40% to ~50%. I’m only mentioning this one here because some anti-hereditarians argue that you can’t trust twin studies because of assortative mating, without mentioning that this can only bias them down. 4: Population stratification: This is often large and worth worrying about, but it applies to identical and fraternal twin pairs equally, and doesn’t bias twin study heritability estimates much (though it might shift the balance between shared and non-shared environment). See eg the sentence around footnote 30 here. 5: Non-additive / “interaction” effects: These are theoretically interesting, but all research thus far has found they are minimal (1, 2). Some experts think this may miss rarer or harder-to-find interactions; we’ll return to this later. 6: “Genetic nurture”, parent-to-child Mentioned above: if there is a gene for reading books to kids, and reading books raises IQ, it will look like a “gene for IQ”. This isn’t as relevant to twin study estimates of heritability, since both identical twins and fraternal twins are equally related to their parents, and any trait caused by genetic nurture wouldn’t differ between them (and therefore would not falsely appear heritable in this design). Rather, they would appear as shared environment. 7: “Genetic nurture”, sibling-to-sibling That is, suppose your sibling’s traits influence your own development. For example, suppose your sibling has a gene that makes them sabotage your schoolwork, causing you to fail and drop out of school early. An identical twin would share this gene with their sibling more often than a fraternal twin, making it look like a “gene for doing badly at school” (since the people who have it do worse at school than those who don’t). Why are we even talking about this? Do we really think it’s a big part of the variance in behavioral traits? Challenging twin study heritability estimates through this route requires inhabiting a weird no-man’s-land where otherwise-invisible genetic and environmental pathways suddenly flare up when you say the magic words “it was done by a sibling”. For example, this requires a strong effect of shared environment - that is, your educational attainment has to depend on whether you’re being sabotaged or not. But in general, shared environmental effects are weak. And it requires a strong effect of genes - that is, this mechanism only works if your sibling’s tendency to sabotage you is highly genetically determined. But we’re deploying this claim to deny that traits like IQ or educational attainment are highly genetically determined. So to get much out of this, the tendency to sabotage siblings would have to be more genetic than other behavioral traits! The reason this convoluted possibility gets brought up so often is that, unlike the more plausible parent-to-child genetic nurture, twin studies can’t rule it out. So if you really want to deny twin studies, this is one of your best bets. But when investigated, this has effects indistinguishable from zero. I’ve been a bit mean in this whole section, because people really like to dismiss twin studies as “Oh, don’t you know, those depend on assumptions, I bet you never considered that assumptions might be wrong”, and then Gish Gallop you with different assumptions until you give up. But scientists have actually done a lot of really good work checking the assumptions and they mostly hold. An alternative way of validating twin studies (brought up by Noah Carl in this article) is to check them against their close cousins, adoption studies and pedigree studies. Pedigree studies investigate large family trees, and check how trait similarity decreases with genetic distance. They avoid twin specific biases (like different treatment of fraternal vs. identical twin pairs, or different prenatal environments), while adding others like assortative mating. Here are the heritabilities of IQ and EA found in pedigree studies10 (see footnote for sources and caveats, and see also here and here for somewhat similar designs): Adoption studies investigate whether adoptees’ traits are more correlated with their adoptive or biological parents. They avoid a large swathe of biases, at the risk of introducing new adoption-related biases of their own (like the possibility that agencies deliberately place adoptive children with parents who are culturally or behaviorally similar, or the possibility that adoptees were adopted late enough to still get some shared environment from their biological parents). Here are the findings of some of the largest and best11: Both straightforwardly confirmed the larger heritability numbers found in twin studies. I would add the evidence from some less formal “adoption studies”12. During residency, I spent a few months working in a child psychiatric hospital for the worst of the worst - kids who committed murder or rape or something before age 18. Many of these children had similar stories: they were taken from their parents just after birth because the parents were criminals/drug addicts/in jail/abusing them. Then they were adopted out to some extremely nice Christian family whose church told them that God wanted them to help poor little children in need. Then they promptly proceeded to commit crime / get addicted to drugs / go to jail / abuse people, all while those families’ biological children were goody-goodies who never got so much as a school detention. When I met with the families, they would always be surprised that things had gone so badly, insisting that they’d raised them exactly like their own son/daughter and taught them good Christian morals. I had to resist the urge to shove a pile of twin studies in their face. This has left me convinced that behavioral traits are highly heritable to a level that it would be hard for any study to contradict. Ultimate source here. Although the study is confusing about this, I think it’s trying to say that almost 90% of subjects were adopted before age 2. But I don’t think studies do contradict this. Given the degree to which their assumptions have been validated, and the level of confirmation from pedigree and adoption studies, I think they have earned a presumption of accuracy. Doubting the twin studies doesn’t seem like a promising route to reconciling the twin-vs-Sib-Regression/RDR discrepancy. What’s Going On? (Part 2: Is Something Wrong With Sib-Regression And RDR?) Sib-Regression is a clever way of avoiding most biases. Its independent variable - the degree to which some sibling pairs end up with slightly more shared genes than others - is even more random and exogenous than the difference between fraternal and identical twins. It can sometimes have biases related to assortative mating (which would falsely push heritability down), but otherwise it’s pretty good. RDR has many of the same advantages, and allows more diverse relationships and so larger sample sizes. It’s hard to think of ways these methods could be wildly off. There is one caveat: although RDR includes most of the rare and structural variants missed by GWAS, in theory it can miss certain ultra-rare variants which are so uncommon that they aren’t shared between some of the relative pairs used in RDR. De novo variants that occurred during the subject’s own conception would be in this category, if the subject didn’t have children or didn’t pass on that gene13. This seems like a pretty small subcategory of genetic variation, and I wouldn’t normally expect that much of importance to be hiding here, but maybe it’s more important than it seems. RDR also doesn’t include much variance caused by statistical interactions between genes. Although we said above that these are usually found to be insignificant, they might be more important in a trait like intelligence that has been under recent evolutionary selection that lops off easily-detectable sources of variance and leaves only the weird obscure ones behind. There’s limited ability for classical Mendelian dominance to affect common variants, but more complicated genetic interactions might still prove important. Overall these are strong methods, and their failure to converge is troubling. If forced to explain them away, we might tell a story like: So far, there is only one RDR study and a few Sib-Regression studies, so we should wait for more data before updating too hard.
Inline links: answer, The best studies, 9, seems real and important, here, 1, 2, when investigated, in this article, 10, here, here, https://substackcdn.com/image/fetch/$s_!b3LF!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc094f9c0-4c71-48cf-89dc-615498d94812_483x51.png, 11, https://substackcdn.com/image/fetch/$s_!XFWU!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F85f433e5-d141-47b7-8dc5-2271925032e9_483x102.png, 12, https://x.com/cremieuxrecueil/status/1935731422205010135, here, 13
Heritability of EA might genuinely vary a lot among different countries, populations, and eras, so maybe we should be less concerned when studies give weird results.
Inline links: eras
I think the post conflates gene-gene and gene-environment interactions; the latter (specifically interactions between genes and the "shared" environment) also get counted by twin models as narrow sense heritability. While I agree there is very little evidence for gene-gene interactions (particularly dominance, as you cite [and, interestingly, twin/adoption studies actually forecast a huge amount of dominance -- another discrepancy we do not understand]) there is quote substantial evidence for gene-environment interactions including on educational attainment (see Cheesman et al: https://www.nature.com/articles/s41539-022-00145-8 ; Mostafavi et al: https://elifesciences.org/articles/48376), IQ, and BMI. In fact, Peter Visscher led a paper that came to the conclusion that twin estimates for the heritability of BMI are very likely to be overestimated by gene-environment interactions (https://pubmed.ncbi.nlm.nih.gov/28692066/). A large amount of GxE plus some amount of equal environment violation seems like a very plausible and parsimonious answer to the heritability gap.
Inline links: https://www.nature.com/articles/s41539-022-00145-8, https://elifesciences.org/articles/48376, https://pubmed.ncbi.nlm.nih.gov/28692066/
Lastly, it's not clear to me where the conclusion that well-validated twin studies converge on "similar results" is coming from. To take one example: the leading lights of behavior genetics (Deary, McGue, Visscher, etc) ran a study looking at the relationship between intelligence and lifespan (https://pubmed.ncbi.nlm.nih.gov/26213105/). This is a nice study for us because they put together three large, modern, twin cohorts with IQ measurements, but the heritability of IQ was just a nuisance parameter for them, so they had no reason to scrutinize the findings or file-drawer them. If we look at their MZ/DZ correlations in Table S6 we find that the heritability of IQ was 0.36 in the US sample; 0.98 in the Swedish sample; 0.24 in the Danish sample; and ... 0.52 on average. In other words, all over the place (but averaging out to the nice "half nature half nurture" result you see in books); the authors themselves used an AE model in Table 2 and reported a range of 0.20 to 0.98. This is far greater than the variability we see with GWAS or Sib-Reg, so what are we to make of that?
Inline links: https://pubmed.ncbi.nlm.nih.gov/26213105/
…Importantly, I think the nature of non-additive genetics is widely misunderstood. If you read the wikipedia article on epistasis, or Zuk et al. 2012, or any other discussion I’ve seen, you’ll get the idea that non-additive genetic effects happen for reasons that are very “organic”—things like genes for two different mutations of the same protein complex, or genes for two enzymes involved in the same metabolic pathway.
When the cracks run that deep, it’s worth going back to the origin story—a landmark 1995 paper by Games et al., featured on the cover of Nature under the headline “A mouse model for Alzheimer’s.” It announced what was hailed as a breakthrough: the first genetically engineered mouse designed to mimic key features of the disease.
Inline links: a landmark 1995 paper by Games
“Mouse Model Made” was the boastful headline to the independent, introductory commentary Nature solicited to accompany the 1995 Games paper’s unveiling of the first transgenic mouse set to “answer the needs” of Alzheimer’s research. The scientific argument over whether amyloid caused Alzheimer’s had been “settle[d]” by the Games paper, “perhaps for good.”
To be considered a valid Alzheimer’s model, the Games mouse needed to express human APP at levels high enough to cause Alzheimer's-like pathology. Previous attempts by other labs had yielded mice that showed little to no amyloid plaques. Scientists suspected that higher expression levels might overcome this hurdle. They introduced the PDGF-β promoter, a genetic “on switch” that controls when and where a gene is activated to drive high expression in neurons; they included introns in the construct to allow for alternative splicing, a process that enables cells to produce different versions of a protein, in this case ensuring expression of the full range of amyloid-beta peptides seen in human Alzheimer’s.
[7] A. W. Bero et al., “Neuronal activity regulates the regional vulnerability to amyloid-β deposition,” Nature Neuroscience, vol. 14, no. 6, pp. 750–756, Jun. 2011, doi: 10.1038/nn.2801.
Inline links: 10.1038/nn.2801
[13] Y. Shi and D. M. Holtzman, “Interplay between innate immunity and Alzheimer disease: APOE and TREM2 in the spotlight,” Nature Reviews Immunology, vol. 18, no. 12, pp. 759–772, Dec. 2018, doi: 10.1038/s41577-018-0051-1.
Inline links: 10.1038/s41577-018-0051-1
[17] S. Palmqvist et al., “Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity,” Nature Communications, vol. 8, no. 1, p. 1214, Oct. 2017, doi: 10.1038/s41467-017-01150-x.
Inline links: 10.1038/s41467-017-01150-x
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