WIRED: Genetic Screening Now Lets Parents Pick the Healthiest Embryos

This is a balanced and informative article in WIRED, excerpted from author Rachael Pells' forthcoming book, Genomics: How Genome Sequencing Will Change Our Lives.

WIRED: ... 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. ...

Two useful references:

Polygenic Health Index, General Health, and Disease Risk 

Complex Trait Prediction: Methods and Protocols (Springer 2022)