Will You Be Among the First to Pick Your Kids' Genes? As machine learning unlocks predictions from DNA databases, scientists say parents could have choices never before possible.
So you don't know who will get it. Treff's grandfather had it, and lost a leg. But Treff's three young kids are fine, so far. He's crossing his fingers they won't develop it later.
Now Treff, an in vitro fertilization specialist, is working on a radical way to change the odds. Using a combination of computer models and DNA tests, the startup company he's working with, Genomic Prediction, thinks it has a way of predicting which IVF embryos in a laboratory dish would be most likely to develop type 1 diabetes or other complex diseases. Armed with such statistical scorecards, doctors and parents could huddle and choose to avoid embryos with failing grades.
IVF clinics already test the DNA of embryos to spot rare diseases, like cystic fibrosis, caused by defects in a single gene. But these "preimplantation" tests are poised for a big leap forward as it becomes possible to look more deeply at an embryo's genome and create broad statistical forecasts about the person it would become.
The advance is occurring, say scientists, thanks to a growing flood of genetic data collected from large population studies. As statistical models known as predictors gobble up information about the DNA and health of hundreds of thousands of people, they're getting more accurate at spotting the genetic patterns that fore-shadow disease risk. But they have a controversial side, since the same techniques can be used to project the eventual height, weight, skin tone, and even intelligence of an IVF embryo.
In addition to Treff, who is the company's chief scientific officer, the founders of Genomic Prediction are Stephen Hsu, a physicist who is vice president for research at Michigan State University, and Laurent Tellier, a Danish bioinformatician who is CEO. Both Hsu and Tellier have been closely involved with a project in China that aims to sequence the genomes of mathematical geniuses, hoping to shed light on the genetic basis of IQ.
The company's plans rely on a tidal wave of new knowledge showing how small genetic differences can add up to make one person, but not another, likely to end up with diabetes, a neurotic personality, or a taller or shorter height. Already, such "polygenic risk scores" are used in direct-to-consumer gene tests, such as reports from 23andMe that tell customers their genetic chance of being overweight.
For adults, risk scores are little more than a novelty. But if the same information is generated about an embryo, it could have existential consequences: who will be born, and who stays in a laboratory freezer?
"I remind my partners, 'You know, if my parents had this test, I wouldn't be here,'" says Treff, a prize-winning expert on diagnostic technology who is the author of more than 90 scientific papers.
Genomic Prediction was founded this year and has raised funds from venture capitalists in Silicon Valley, though it declines to say who they are. Tellier says the company plans to offer reports to IVF doctors and parents identifying "outliers"--those embryos whose genetic scores put them at the wrong end of a statistical curve for disorders such as diabetes, late-life osteoporosis, schizophrenia, and dwarfism, depending on whether models for those problems prove accurate.
The company's concept, which it calls expanded preimplantation genetic testing, or ePGT, would effectively add a range of common disease risks to the menu of rare ones already available, which it also plans to test for. Its promotional material uses a picture of a mostly submerged iceberg to get the idea across. "We believe it will become a standard part of the IVF process," says Tellier, just as a test for Down syndrome is a standard part of pregnancy.
Some experts say it's premature to introduce polygenic scoring technology into IVF clinics--though perhaps not by very much. Matthew Rabinowitz, CEO of the California-based prenatal-testing company Natera, says he thinks predictions obtained today could be 'largely misleading" because DNA models don't function well enough. But Rabinowitz agrees that the technology is coming along.
"You are not going to stop the modeling in genetics, and you are not going to stop people from accessing it," he says. "It's going to get better and better."
Testing embryos for disease risks, including risks for diseases that develop only late in life, is considered ethically acceptable by U.S. fertility doctors. But the new DNA scoring models mean parents might be able to choose their kids on the basis of traits like IQ or adult weight. That's because, just like type 1 diabetes, these traits are the result of complex genetic influences the predictor algorithms are designed to find.
"It's the camel's nose under the tent. Because if you are doing it for something more serious, then it's trivially easy to look for anything else," says Michelle Meyer, a bioethicist at the Geisinger Health System who analyzes issues in reproductive genetics. "Here is the genomic dossier on each embryo. And you flip through the book." Imagine picking the embryo most likely to get into Harvard like Mom, or to be tall like Dad.
For Genomic Prediction, a tiny startup based at a tech incubator in New Jersey, such questions will be especially sharply drawn. That is because of Hsu's long-standing interest in genetic selection for superior intelligence. In 2014, Hsu authored an essay titled "Super-Intelligent Humans Are Coming," in which he argued that selecting embryos for intelligence could boost the resulting child's IQ by 15 points.
Genomic Prediction says it will only report diseases--that is, identify those embryos it thinks would develop into people with serious medical problems. Even so, on his blog and in public statements, Hsu has for years been developing a vision that goes far beyond that.
"Suppose I could tell you embryo four is going to be the tallest, embryo three is going to be the smartest, embryo two is going to be very antisocial. Suppose that level of granularity was available in the reports," he told the conservative radio personality Stefan Molyneux this spring. "That is the near-term future that we as a civilization face. This is going to be here."
The fuel for the predictive models is a deluge of new data, most recently genetic readouts and medical records for 500,000 middle-aged Britons that were released in July by the UK Biobank, a national precision-medicine project.
The data trove included, for each volunteer, a map of about 800,000 single-nucleotide polymorphisms, or SNPs--points where their DNA differs slightly from another person's. The release caused a pell-mell rush by geneticists to update their calculations about exactly how much of human disease, or even routine behaviors like bread consumption, these genetic differences could explain.
Armed with the U.K. data, Hsu and Tellier claimed a breakthrough. For one easily measured trait, height, they used machine-learning techniques to create a predictor. They reported that their model could, for the most part, predict people's height from their DNA data to within three or four centimeters.
Tellier says Genomic Prediction will zero in on disease traits for which the predictors already perform fairly well, or will soon. Those include autoimmune disorders like the illness Treff suffers from. In those conditions, a smaller set of genes dominates the predictions, sometimes making them more reliable.
The company doesn't intend to give out raw trait scores to parents, only to flag embryos likely to be abnormal. That is because the product has to be "ethically defensible," says Hsu: "We would only reveal the negative outlier state. We don't report, 'This guy is going to be in the NBA.'"
But by now, polygenic scores have become a routine aspect of DNA tests. A company called HumanCode sells a $199 test that uses SNP scores to tell people how tall their kids might be. In the dairy cattle industry, polygenic tests are used to rate animals for how much milk they'll produce.
Some scientists doubt the scores will prove useful at picking better people from IVF dishes. Even if they're accurate on the average, for individuals there's no guarantee of pinpoint precision. What's more, environment has as big an impact on most traits as genes do. "There is a high probability that you will get it wrong--that would be my concern," says Manuel Rivas, a professor at Stanford University who studies the genetics of Crohn's disease.
"If someone is using that information to make decisions about embryos, I don't know what to make of it." Efforts to introduce this type of statistical scoring into reproduction have drawn criticism in the past. In 2013, 23 and Me provoked outrage when it won a patent on the idea of drop-down menus parents could use to pick sperm or egg donors--say, to try to get a specific eye color. The company, funded by Google, quickly backpedaled.
Genomic Prediction recently staffed a booth at the annual meeting of the American Society for Reproductive Medicine. That organization, which represents fertility doctors and scientists, has previously said it thinks testing embryos for late-life conditions, like Alzheimer's, would be "ethically justified." It cited, among other reasons, the "reproductive liberty" of parents. It has been more ambivalent about choosing the sex of embryos, leaving that to the discretion of doctors.
Hsu thinks intelligence is "the most interesting phenotype," or trait, of all. But when he tried his predictor to see what it could say about how far along in school the 500,000 subjects from the UK Biobank had gotten (years of schooling is a proxy for IQ), he found that DNA couldn't predict it nearly as well as it could predict height.
Hsu anticipates that "billionaires and Silicon Valley types" will be the early adopters of embryo selection technology, becoming among the first "to do IVF even though they don't need IVF." As they start producing fewer unhealthy children, and more exceptional ones, the rest of society could follow suit.
"I fully predict it will be possible," he says of selecting embryos with higher IQ scores. "But we've said that we as a company are not going to do it. It's a difficult issue, like nuclear weapons or gene editing. There will be some future debate over whether this should be legal, or made illegal. Countries will have referendums on it."
"This would completely change her world."
--Brett Kopelan, executive director of the Dystrophic Epidermolysis Bullosa Research Association of America, on the potential of gene therapy to help his 10-year-old daughter and others with devastating skin disorders.
--Tomaso Poggio, a professor at the McGovern Institute for Brain Research, on the hype surrounding artificial intelligence.
--Park Williams, a bioclimatologist at Columbia University, on the effect of climate change on wildfires.
BY THE NUMBERS
Number of countries where social media was used to influence elections in 2017, according to the democracy advocacy group Freedom Now.
Number of operations a man named Brian Madeux has undergone for complications related to Hunter syndrome. In November Madeux became the first person to officially have gene editing take place inside his body, via a treatment from Sangamo Therapeutics.
Proportion of jobs created since 2010 that require at least moderate digital skills, according to a November report from the Brookings Institution.
Number of the world's 500 fastest supercomputers that are currently located in China. The U.S., in comparison, has 144 of them.
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|Title Annotation:||Upfront; Genomic Prediction company|
|Publication:||MIT Technology Review|
|Date:||Jan 1, 2018|
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