Genetic Screening Now Lets Parents Pick the Healthiest Embryos

People using IVF can see which embryo is least likely to develop cancer and other diseases. But can protecting your child slip into playing God?
ultrasound of embryo
Photograph: Albert Martine/Getty Images

At 18 months old, Aurea Yenmai Smigrodzki is inquisitive like any other toddler. She likes peanut butter, the beach, and mobile phones—or any toys that look like phones. She likes to copy her mum and dad, Thuy and Rafal, when they are using theirs. Aurea doesn’t know it yet, but her birth was very special: She is the world’s first PGT-P baby, meaning she is statistically less likely than the rest of us to develop a genetic disease or disorder throughout her life.

PGT-P stands for preimplantation genetic testing for polygenic disorders. It is conducted in conjunction with IVF and allows prospective parents to actively select which of their own embryos to take, based on the strength of its genes. Rafal and Thuy were given the genetic profiles of five prospective embryos, and Aurea’s was the strongest candidate, because her embryo had the fewest recognizable genetic mutations that could go on to cause disease. “It was really a no-brainer,” says Rafal of the choice he and Thuy made to undergo the genetic screening process. “If you can do something good for your child, you want to do it, right? That’s why people take prenatal vitamins.”

All parents want their children to be healthy, but lots have reason to fear passing on something harmful. Our genes can predispose us to developing all kinds of diseases: diabetes, heart disease, cancers, and many more. With this in mind, one could be forgiven for assuming that Rafal or Thuy carried some inheritable condition and wanted to break the chain. But the reality, Rafal admits, is that he “simply knew that PGT-P existed,” and so he decided to give it a try.

Rafal is a neurologist and has an interest in pioneering technologies, referring to himself as a “techno-optimist.” He has even signed up to have his brain cryogenically stored when he dies, in the belief it will one day be resurrected, thoughts and spirit intact. In his eyes, genetic screening of embryos is nothing crazy or even special, it is simply the natural next step for humans to take. “It’s like the first time someone ever made a phone call—sure, it was a unique moment, but really it was just the beginning of something that now everybody does,” Rafal muses. “In 10 years’ time, this kind of polygenic testing will be completely non-controversial. People will be doing it as a matter of course.”

Thuy and Rafal screened their embryos through Genomic Prediction, the first of a couple of biotech firms in the US to open up genetic screening services to prospective parents. Taking DNA samples from the embryo cells alongside genetic sequences from both parents, analysts are able to draw up a set of markers from which they can construct a full genetic picture of the embryo. This effectively fast-forwards its development process to create a projection of what level of health a child born with those genes might enjoy. To help their clients put this data into context, each embryo is given a health score based on the existing mutations in its genes which could potentially one day be life limiting, and the would-be parents are shown how that score compares against the population average. The ranking takes into account the severity of conditions, if shown, as well as the ethnicity of the embryo, since this can also have an impact on disease incidence.

Aurea is the product of that ranking: she was the top-rated embryo out of Thuy and Rafal’s IVF collection and the cells they chose to give the best possible chance at living a long, disease-free life. When Aurea is older, she will have access to the full set of embryonic screening data shared with her parents. She will probably have her own genome sequenced, too—Rafal has already purchased a home testing kit for her—and use that information to guide her approach to health and lifestyle through her life. “I hope she will be glad for it,” says Rafal.

“People ask me if I’m trying to play God in choosing to do this,” Rafal adds, anticipating the next big question. He believes that “genetic selection is not playing God, it’s working as a mechanic on molecular machines that sometimes break and need to be fixed.” Of course, good genes are by no means a guarantee for a long and healthy life, and carrying an abnormality or even living with a hereditary disease does not always equate to a poorer quality of life. Rafal does not for a moment believe that passing on unhealthy genes makes someone a bad parent, either. But he is unequivocal in his belief that he has done the best thing for his child by giving her the best odds against genetic disease. “As parents, we act as the health champions of our children, and it makes sense to treat genes not as mysterious determinants of identity, but something that you know is there and is important; these are the same principles I apply in trying to take good care of my own health. What matters,” he continues, “is that the process was successful, my child was born healthy, and she is happy.”

Polygenic risk scores (also referred to as a genetic risk score) were used by Genomic Prediction in the case of Rafal, Thuy, and Aurea to indicate the likelihood of gene mutations among multiple embryos. They are also a marker used in other areas of biology to determine roughly how one organism’s genetic health compares to another’s. For example, polygenic scores are commonly used in animal and plant breeding to improve the chances of having healthy and resilient livestock and crops. The “score” is calculated from the number of variations found in each organism’s genome that relate to a particular disease (therefore increasing the risk of developing it). This is compared against a reference database compiled from large-scale population studies in order to provide a relative indicator of how likely that organism is to develop a disease relative to the average.

There are no guarantees in using this process: it can only be used as a forecast, because the score only compares to an average organism rather than testing for genetic links to disease in each individual. Neither does it take into consideration environmental factors. For example, a 21-year-old and a 99-year-old could have the same polygenic risk score if their genes predispose them to having coronary heart disease, but the score doesn’t account for where they are in their lifespan or when they might present with the disease. So, the indicators are limited, but they can show with accuracy what common genetic conditions a person or organism might be carrying—which is relevant to parents selecting one embryo out of several.

Embryonic selection itself is nothing new. For around three decades, IVF clinicians have taken sperm and egg samples to grow into several embryos at once, before choosing the most promising-looking one for implantation in the uterus. Clinics already tend to screen against chromosomal abnormalities such as Down’s syndrome, but until recently the only other indicator they had to go by was the way one group of cells looked against the other—the selection was more or less arbitrary.

Companies such as Genomic Prediction are taking this process much further, giving parents the power to select the embryo they believe to have the best fighting chance of survival both in the womb and out in the world. At the time of writing, Genomic Prediction works with around 200 IVF clinics across six continents. For company cofounder Stephen Hsu, the idea behind preconception screening was no eureka moment, but something he and his peers developed gradually. “We kept pursuing the possibilities from a purely scientific interest,” he says. Over time sequencing has become cheaper and more accessible, and the bank of genetic data has become ever greater, which has provided the opportunity to easily apply machine learning programs to seek out patterns, Hsu explains. “You can have typically millions of people in one data set, with exact measurements of certain things about them—for instance how tall they are or whether they have diabetes—what we call phenotypes. And so it’s relatively straightforward to use AI to build genetic predictors of traits ranging from very simple ones which are only determined by a few genes, or a few different locations in the genome, to the really complicated ones.” As Hsu indicates, the crucial difference with this technology is that it’s not just single mutations like cystic fibrosis or sickle cell anemia that the service makes its calculations on. The conditions embryos are screened for can be extremely complicated, involving thousands of genetic variants across different parts of the genome.

In late 2017, Hsu and his colleagues published a paper demonstrating how, using genomic data at scale, scientists could predict someone’s height to within an inch of accuracy using just their DNA. The research group later used the same method to build genomic predictors for complex diseases such as hypothyroidism, types 1 and 2 diabetes, breast cancer, prostate cancer, testicular cancer, gallstones, glaucoma, gout, atrial fibrillation, high cholesterol, asthma, basal cell carcinoma, malignant melanoma, and heart attacks. This did not come without controversy. In fact, by mid-2020, the outrage among graduate students at Michigan State University was loud enough to force Hsu out of his position as vice president at the institution. Hsu believes that the opposition people felt to Genomic Prediction in the beginning was largely because people feel uneasy about the fact that genetics can seal our fate—that unfavorable traits can’t always be amended through hard work and determination. “People don’t want to believe that there’s some degree of hardwiring that can’t be overcome by good habits or good education,” he says. “But the fear is misplaced: the ability to detect single gene mutations has been around for some time and nobody considers that ethically questionable, right? It’s just that now we can do it with more precision.”

Studies by Genomic Prediction show that children born through the service have a 46 percent lower risk of heart attack, 42 percent less chance of getting type 2 diabetes, 15 percent reduction in risk of breast cancer and 34 percent lower risk of schizophrenia. “Using genomic predictors we can easily find people who are at 10 times the normal risk. We can easily find people who are 10 times below normal risk. And that’s a huge piece of progress,” says Hsu.

Like Rafal Smigrodzki, Hsu is confident that public disapproval will ease, and that one day soon embryonic selection against inheritable diseases will be considered the norm. In his opinion, “we shouldn’t only use artificial ways to reproduce, but we should make use of the tools we have for IVF to ensure we have the best chance of making healthy babies.”

It’s not just Genomic Prediction that is in the market. Other businesses are now offering screening services aimed at prospective parents. One, MyOme, is conducting trials with doctors and IVF patients, the results of which will determine their plans to open to clients. Orchid, a San Francisco–based startup, launched its waiting list for at-home DNA testing kits in spring 2021 aimed at couples who are looking to have children. The service promises a report detailing risks for any future children and separate male and female partner reports.

One aspect of Genomic Prediction’s work that few would criticize, and shouldn’t be overlooked, is screening to improve the chances of a healthy pregnancy. In screening for healthy embryos, clinicians are also reducing the chances of complications during pregnancy which can result from genetic factors, and helping couples to save time, money, and a lot of heartache. But advancements in genomics are facilitating other ways of improving the conception process for couples, too. In 2013, a biotech company called Natera became the first to develop a panoramic blood test to screen for fetal abnormalities from as early as nine weeks into pregnancy.

The noninvasive prenatal test (NIPT) replaces traditional chorionic villus sampling (CVS)—an unpleasant test involving a large needle to extract cells from the placenta—in screening for chromosomal conditions such as Down’s syndrome, Edwards’ syndrome or Patau’s syndrome.

CVS was effective in detecting abnormalities, but increased the risk of miscarriage by around 1 percent; NIPT, being noninvasive, is much safer. Like so many life-changing inventions, the first NIPT came about because of a personal experience. Natera’s cofounder and chair Matthew Rabinowitz explains that, in 2003, his sister gave birth to a son who had severe chromosomal abnormalities. Tragically, the baby died at six days old, an experience Rabinowitz says was “overwhelmingly upsetting. I’m an engineer and my nature is to solve problems. And this was a situation that was just not fixable.” The family felt blindsided: “He was born in a top hospital in Boston, and yet they didn’t realize that he had these problems until he was born,” says Rabinowitz. “I thought, ‘How could this happen in the 21st century?’ There’s got to be a way to improve on these technologies.”

At the time, Rabinowitz was a professor in aeronautics and astronautics at Stanford University, and dealt with the shock and grief in the best way he knew how: by throwing himself into new research. His team began work on genetic techniques to look at tiny amounts of DNA that could extract “a much more powerful signal” of the health and development of a fetus. Rabinowitz submitted the resulting data to the National Institutes of Health (the US’s publicly funded medical research agency), which awarded him a startup business grant—and the rest is history. NIPT works by sequencing small fragments of fetal DNA (cfDNA) that can be detected in the mother’s blood.

The cfDNA is isolated and examined to detect aneuploidies—where an abnormal number of chromosomes is present in each cell—but also, if the doctor requests, some of the single-gene variations which cause severe genetic diseases. Since biological sex is determined by chromosomes, the blood test can also identify the fetus’s sex much earlier than an ultrasound. Different brands of NIPT have since been developed and rolled out across the world in both public and private healthcare. “It’s completely changed the way people all over the world manage pregnancy,” says Rabinowitz.

Rachael Pells is the author of Genomics: How Genome Sequencing Will Change Our Lives. Find out more and order your copy of the book.

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