Genetic Test Scores Predicting Intelligence Are Not the New Eugenics
"A world where people are slotted according to their inborn ability – well, that is Gattaca. That is eugenics."
This was the assessment of Dr. Catherine Bliss, a sociologist who wrote a new book on social science genetics, when asked by MIT Technology Review about polygenic scores that can predict a person's intelligence or performance in school. Like a credit score, a polygenic score is statistical tool that combines a lot of information about a person's genome into a single number. Fears about using polygenic scores for genetic discrimination are understandable, given this country's ugly history of using the science of heredity to justify atrocities like forcible sterilization. But polygenic scores are not the new eugenics. And, rushing to discuss polygenic scores in dystopian terms only contributes to widespread public misunderstanding about genetics.
Can we start genotyping toddlers to identify the budding geniuses among them? The short answer is no.
Let's begin with some background on how polygenic scores are developed. In a genome wide-association study, researchers conduct millions of statistical tests to identify small differences in people's DNA sequence that are correlated with differences in a target outcome (beyond what can attributed to chance or ancestry differences). Successful studies of this sort require enormous sample sizes, but companies like 23andMe are now contributing genetic data from their consumers to research studies, and national biorepositories like U.K. Biobank have put genetic information from hundreds of thousands of people online. When applied to studying blood lipids or myopia, this kind of study strikes people as a straightforward and uncontroversial scientific tool. But it can also be conducted for cognitive and behavioral outcomes, like how many years of school a person has completed. When researchers have finished a genome-wide association study, they are left with a dataset with millions of rows (one for each genetic variant analyzed) and one column with the correlations between each variant and the outcome being studied.
The trick to polygenic scoring is to use these results and apply them to people who weren't participants in the original study. Measure the genes of a new person, weight each one of her millions of genetic variants by its correlation with educational attainment from a genome-wide association study, and then simply add everything up into a single number. Voila! -- you've created a polygenic score for educational attainment. On its face, the idea of "scoring" a person's genotype does immediately suggest Gattaca-type applications. Can we now start screening embryos for their "inborn ability," as Bliss called it? Can we start genotyping toddlers to identify the budding geniuses among them?
The short answer is no. Here are four reasons why dystopian projections about polygenic scores are out of touch with the current science:
The phrase "DNA tests for IQ" makes for an attention-grabbing headline, but it's scientifically meaningless.
First, a polygenic score currently predicts the life outcomes of an individual child with a great deal of uncertainty. The amount of uncertainty around polygenic predictions will decrease in the future, as genetic discovery samples get bigger and genetic studies include more of the variation in the genome, including rare variants that are particular to a few families. But for now, knowing a child's polygenic score predicts his ultimate educational attainment about as well as knowing his family's income, and slightly worse than knowing how far his mother went in school. These pieces of information are also readily available about children before they are born, but no one is writing breathless think-pieces about the dystopian outcomes that will result from knowing whether a pregnant woman graduated from college.
Second, using polygenic scoring for embryo selection requires parents to create embryos using reproductive technology, rather than conceiving them by having sex. The prediction that many women will endure medically-unnecessary IVF, in order to select the embryo with the highest polygenic score, glosses over the invasiveness, indignity, pain, and heartbreak that these hormonal and surgical procedures can entail.
Third, and counterintuitively, a polygenic score might be using DNA to measure aspects of the child's environment. Remember, a child inherits her DNA from her parents, who typically also shape the environment she grows up in. And, children's environments respond to their unique personalities and temperaments. One Icelandic study found that parents' polygenic scores predicted their children's educational attainment, even if the score was constructed using only the half of the parental genome that the child didn't inherit. For example, imagine mom has genetic variant X that makes her more likely to smoke during her pregnancy. Prenatal exposure to nicotine, in turn, affects the child's neurodevelopment, leading to behavior problems in school. The school responds to his behavioral problems with suspension, causing him to miss out on instructional content. A genome-wide association study will collapse this long and winding causal path into a simple correlation -- "genetic variant X is correlated with academic achievement." But, a child's polygenic score, which includes variant X, will partly reflect his likelihood of being exposed to adverse prenatal and school environments.
Finally, the phrase "DNA tests for IQ" makes for an attention-grabbing headline, but it's scientifically meaningless. As I've written previously, it makes sense to talk about a bacterial test for strep throat, because strep throat is a medical condition defined as having streptococcal bacteria growing in the back of your throat. If your strep test is positive, you have strep throat, no matter how serious your symptoms are. But a polygenic score is not a test "for" IQ, because intelligence is not defined at the level of someone's DNA. It doesn't matter how high your polygenic score is, if you can't reason abstractly or learn from experience. Equating your intelligence, a cognitive capacity that is tested behaviorally, with your polygenic score, a number that is a weighted sum of genetic variants discovered to be statistically associated with educational attainment in a hypothesis-free data mining exercise, is misleading about what intelligence is and is not.
The task for many scientists like me, who are interested in understanding why some children do better in school than other children, is to disentangle correlations from causation.
So, if we're not going to build a Gattaca-style genetic hierarchy, what are polygenic scores good for? They are not useless. In fact, they give scientists a valuable new tool for studying how to improve children's lives. The task for many scientists like me, who are interested in understanding why some children do better in school than other children, is to disentangle correlations from causation. The best way to do that is to run an experiment where children are randomized to environments, but often a true experiment is unethical or impractical. You can't randomize children to be born to a teenage mother or to go to school with inexperienced teachers. By statistically controlling for some of the relevant genetic differences between people using a polygenic score, scientists are better able to identify potential environmental causes of differences in children's life outcomes. As we have seen with other methods from genetics, like twin studies, understanding genes illuminates the environment.
Research that examines genetics in relation to social inequality, such as differences in higher education outcomes, will obviously remind people of the horrors of the eugenics movement. Wariness regarding how genetic science will be applied is certainly warranted. But, polygenic scores are not pure measures of "inborn ability," and genome-wide association studies of human intelligence and educational attainment are not inevitably ushering in a new eugenics age.
DNA- and RNA-based electronic implants may revolutionize healthcare
Implantable electronic devices can significantly improve patients’ quality of life. A pacemaker can encourage the heart to beat more regularly. A neural implant, usually placed at the back of the skull, can help brain function and encourage higher neural activity. Current research on neural implants finds them helpful to patients with Parkinson’s disease, vision loss, hearing loss, and other nerve damage problems. Several of these implants, such as Elon Musk’s Neuralink, have already been approved by the FDA for human use.
Yet, pacemakers, neural implants, and other such electronic devices are not without problems. They require constant electricity, limited through batteries that need replacements. They also cause scarring. “The problem with doing this with electronics is that scar tissue forms,” explains Kate Adamala, an assistant professor of cell biology at the University of Minnesota Twin Cities. “Anytime you have something hard interacting with something soft [like muscle, skin, or tissue], the soft thing will scar. That's why there are no long-term neural implants right now.” To overcome these challenges, scientists are turning to biocomputing processes that use organic materials like DNA and RNA. Other promised benefits include “diagnostics and possibly therapeutic action, operating as nanorobots in living organisms,” writes Evgeny Katz, a professor of bioelectronics at Clarkson University, in his book DNA- And RNA-Based Computing Systems.
While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output.
Adamala’s research focuses on developing such biocomputing systems using DNA, RNA, proteins, and lipids. Using these molecules in the biocomputing systems allows the latter to be biocompatible with the human body, resulting in a natural healing process. In a recent Nature Communications study, Adamala and her team created a new biocomputing platform called TRUMPET (Transcriptional RNA Universal Multi-Purpose GatE PlaTform) which acts like a DNA-powered computer chip. “These biological systems can heal if you design them correctly,” adds Adamala. “So you can imagine a computer that will eventually heal itself.”
The basics of biocomputing
Biocomputing and regular computing have many similarities. Like regular computing, biocomputing works by running information through a series of gates, usually logic gates. A logic gate works as a fork in the road for an electronic circuit. The input will travel one way or another, giving two different outputs. An example logic gate is the AND gate, which has two inputs (A and B) and two different results. If both A and B are 1, the AND gate output will be 1. If only A is 1 and B is 0, the output will be 0 and vice versa. If both A and B are 0, the result will be 0. While a computer gives these inputs in binary code or "bits," such as a 0 or 1, biocomputing uses DNA strands as inputs, whether double or single-stranded, and often uses fluorescent RNA as an output. In this case, the DNA enters the logic gate as a single or double strand.
If the DNA is double-stranded, the system “digests” the DNA or destroys it, which results in non-fluorescence or “0” output. Conversely, if the DNA is single-stranded, it won’t be digested and instead will be copied by several enzymes in the biocomputing system, resulting in fluorescent RNA or a “1” output. And the output for this type of binary system can be expanded beyond fluorescence or not. For example, a “1” output might be the production of the enzyme insulin, while a “0” may be that no insulin is produced. “This kind of synergy between biology and computation is the essence of biocomputing,” says Stephanie Forrest, a professor and the director of the Biodesign Center for Biocomputing, Security and Society at Arizona State University.
Biocomputing circles are made of DNA, RNA, proteins and even bacteria.
Evgeny Katz
The TRUMPET’s promise
Depending on whether the biocomputing system is placed directly inside a cell within the human body, or run in a test-tube, different environmental factors play a role. When an output is produced inside a cell, the cell's natural processes can amplify this output (for example, a specific protein or DNA strand), creating a solid signal. However, these cells can also be very leaky. “You want the cells to do the thing you ask them to do before they finish whatever their businesses, which is to grow, replicate, metabolize,” Adamala explains. “However, often the gate may be triggered without the right inputs, creating a false positive signal. So that's why natural logic gates are often leaky." While biocomputing outside a cell in a test tube can allow for tighter control over the logic gates, the outputs or signals cannot be amplified by a cell and are less potent.
TRUMPET, which is smaller than a cell, taps into both cellular and non-cellular biocomputing benefits. “At its core, it is a nonliving logic gate system,” Adamala states, “It's a DNA-based logic gate system. But because we use enzymes, and the readout is enzymatic [where an enzyme replicates the fluorescent RNA], we end up with signal amplification." This readout means that the output from the TRUMPET system, a fluorescent RNA strand, can be replicated by nearby enzymes in the platform, making the light signal stronger. "So it combines the best of both worlds,” Adamala adds.
These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body.
The TRUMPET biocomputing process is relatively straightforward. “If the DNA [input] shows up as single-stranded, it will not be digested [by the logic gate], and you get this nice fluorescent output as the RNA is made from the single-stranded DNA, and that's a 1,” Adamala explains. "And if the DNA input is double-stranded, it gets digested by the enzymes in the logic gate, and there is no RNA created from the DNA, so there is no fluorescence, and the output is 0." On the story's leading image above, if the tube is "lit" with a purple color, that is a binary 1 signal for computing. If it's "off" it is a 0.
While still in research, TRUMPET and other biocomputing systems promise significant benefits to personalized healthcare and medicine. These organic-based systems could detect cancer cells or low insulin levels inside a patient’s body. The study’s lead author and graduate student Judee Sharon is already beginning to research TRUMPET's ability for earlier cancer diagnoses. Because the inputs for TRUMPET are single or double-stranded DNA, any mutated or cancerous DNA could theoretically be detected from the platform through the biocomputing process. Theoretically, devices like TRUMPET could be used to detect cancer and other diseases earlier.
Adamala sees TRUMPET not only as a detection system but also as a potential cancer drug delivery system. “Ideally, you would like the drug only to turn on when it senses the presence of a cancer cell. And that's how we use the logic gates, which work in response to inputs like cancerous DNA. Then the output can be the production of a small molecule or the release of a small molecule that can then go and kill what needs killing, in this case, a cancer cell. So we would like to develop applications that use this technology to control the logic gate response of a drug’s delivery to a cell.”
Although platforms like TRUMPET are making progress, a lot more work must be done before they can be used commercially. “The process of translating mechanisms and architecture from biology to computing and vice versa is still an art rather than a science,” says Forrest. “It requires deep computer science and biology knowledge,” she adds. “Some people have compared interdisciplinary science to fusion restaurants—not all combinations are successful, but when they are, the results are remarkable.”
In today’s podcast episode, Leaps.org Deputy Editor Lina Zeldovich speaks about the health and ecological benefits of farming crickets for human consumption with Bicky Nguyen, who joins Lina from Vietnam. Bicky and her business partner Nam Dang operate an insect farm named CricketOne. Motivated by the idea of sustainable and healthy protein production, they started their unconventional endeavor a few years ago, despite numerous naysayers who didn’t believe that humans would ever consider munching on bugs.
Yet, making creepy crawlers part of our diet offers many health and planetary advantages. Food production needs to match the rise in global population, estimated to reach 10 billion by 2050. One challenge is that some of our current practices are inefficient, polluting and wasteful. According to nonprofit EarthSave.org, it takes 2,500 gallons of water, 12 pounds of grain, 35 pounds of topsoil and the energy equivalent of one gallon of gasoline to produce one pound of feedlot beef, although exact statistics vary between sources.
Meanwhile, insects are easy to grow, high on protein and low on fat. When roasted with salt, they make crunchy snacks. When chopped up, they transform into delicious pâtes, says Bicky, who invents her own cricket recipes and serves them at industry and public events. Maybe that’s why some research predicts that edible insects market may grow to almost $10 billion by 2030. Tune in for a delectable chat on this alternative and sustainable protein.
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Further reading:
More info on Bicky Nguyen
https://yseali.fulbright.edu.vn/en/faculty/bicky-n...
The environmental footprint of beef production
https://www.earthsave.org/environment.htm
https://www.watercalculator.org/news/articles/beef-king-big-water-footprints/
https://www.frontiersin.org/articles/10.3389/fsufs.2019.00005/full
https://ourworldindata.org/carbon-footprint-food-methane
Insect farming as a source of sustainable protein
https://www.insectgourmet.com/insect-farming-growing-bugs-for-protein/
https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/insect-farming
Cricket flour is taking the world by storm
https://www.cricketflours.com/
https://talk-commerce.com/blog/what-brands-use-cricket-flour-and-why/
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.