Skip to Content

Picking the Best Embryo from the Bunch

New embryo-screening technologies could weed out embryos with major genetic abnormalities and improve IVF success rates.
January 9, 2007

More and more of the thousands of women undergoing in vitro fertilization (IVF) are asking their doctors for preimplantation genetic screening, a special type of embryo testing designed to weed out embryos with abnormal chromosomes. Such embryos are less likely to lead to successful pregnancies–they either fail to implant or miscarry, or if they do come to term, they can produce babies with disabilities such as Down’s syndrome. Current screening techniques can only detect a subset of abnormal embryos, and doctors disagree about whether the screening substantially improves a patient’s chance of pregnancy. But new screening technologies about to hit the market could change that, potentially bringing a big boost in IVF success rates.

Scientists remove a single cell from an embryo derived from in vitro fertilization so that it can be used for genetic screening.

About 50 percent of human embryos are chromosomally abnormal, meaning they carry either one or three copies of a chromosome, rather than the typical two, or they have a chromosome with an abnormal structure. This percentage increases with a woman’s age–it’s up to 80 percent in women over 40. “We think the majority of IVF procedures that fail do so because of chromosomal abnormalities,” says David Adamson, incoming president of the American Society for Reproductive Medicine.

Chromosome screening is just one type of genetic test available for embryo screening; others include tests for genetic diseases such as cystic fibrosis. But chromosome screening is by far the most common, accounting for about two-thirds of preimplantation genetic testing. Despite its popularity, however, such tests are controversial. Studies comparing the successful-pregnancy rates of those who have had their embryos screened with those who have not have produced conflicting results.

Current screening methods use specially designed fluorescent probes that bind to the different chromosomes, revealing if there are either extra copies or not enough. But only 10 to 12 different probes can be used at a time, meaning that about half of the embryo’s 23 chromosome pairs go unscreened. “So you’re probably still transferring embryos that are abnormal,” says David Grainger, president of the Society for Assisted Reproductive Technology.

New methods that use DNA microarrays–small chips coated with specific DNA sequences–could provide a more accurate screening method because researchers can simultaneously analyze many more spots on the chromosomes. But the major barrier to using microarrays to analyze embryonic DNA is generating enough genetic material for the test. The single cell used for genetic screening, which scientists carefully remove from the embryo, contains far too little DNA for the tests. And the most common duplication method, known as the polymerase chain reaction, is too error prone to be used in this case.


William Kearns, director of the Shady Grove Center for Preimplantation Genetic Diagnosis, a commercial genetic-testing center in Washington, D.C., and his colleagues have developed a more accurate amplification technique. Kearns is now developing a specialized microarray that will detect not only chromosomal abnormalities, but also several other genetic characteristics, including small duplications or deletions of DNA and genetic variations linked to single-gene disorders, which are currently detected with another method. “I think being able to look at all these things will increase chances of having a successful pregnancy,” says Kearns. “Eventually, I think everyone undergoing IVF will do it.” So far, Kearns has tested the technology on genetically abnormal embryos donated for research. He expects the test to be clinically available in three to six months.

This type of methodology should also improve error rates, says Santiago Munnes, director of Reprogenetics, a genetic-testing laboratory in Livingstone, NY. Munnes’s team is developing a similar set of new screening tools. Because laboratories have only a single cell to work with, they can’t repeat tests for accuracy, and error rates vary widely, depending on how the cell is prepared and who is running the test. In addition, the current screening method analyzes only one spot on the chromosome, while microarray tests could analyze four to five spots per chromosome.

It’s not yet clear how much such tests will cost. Munnes’s team plans to develop a relatively simple test designed to detect 100 to 150 genetic markers, and he hopes it will be in the same price range–about $2,000–as the current test. Kearns is developing a more extensive test, examining 500,000 markers per embryo, which is likely to be more expensive. It will also collect much more genetic information, including information that won’t be immediately useful but may aid in predicting complex diseases as the child grows older and scientists better understand the genetics of these illnesses.

The new tools will need extensive testing before doctors know how helpful they are and in what group of patients they may be most successful. (Unlike drugs, there is little regulation outlining the types of clinical testing necessary before a product can be sold in the clinic.) “I am very hopeful that the technology is going to improve to the point where it will be very effective and helpful in improving pregnancy rates in IVF patients,” says Adamson. “But we still have more research to do.”

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.