Yet the availability today of genetic data for many thousands of individuals, thanks to the plummeting costs of genome sequencing and the popularity of genomic profiling companies such as 23AndMe and Orchid, has transformed our understanding of how genes relate to traits. The technique known as a genome-wide association study (GWAS) can sift through vast databanks to look for statistical associations between an individual’s gene variants and pretty much any trait we choose. Such studies have found that often substantial amounts of the differences between individuals can be linked to different variants (alleles) of many genes. Each gene might contribute only a tiny effect – too small to be apparent without plenty of data – but added together, the influence of the genes can be significant.

So someone’s genetic profile – the variants in their personal genome – can be used to make predictions about, say, how likely they are to develop heart disease in later life. They can be assigned a so-called polygenic risk score (PRS) for that condition. Aurea’s embryo was chosen because of low PRSs for heart disease, diabetes and cancer. PRSs can be used to predict other things too, such as a child’s IQ and educational attainment.

But such predictions are probabilistic, both because we can’t say exactly how our genes will “play out” in influencing that trait and because genes aren’t the only influence anyway. So there’s nothing inevitable or deterministic about a PRS. An individual with a high PRS for skin cancer might never develop it, while someone who scores low might do so. Someone with a genetic profile that predicts a modest IQ might turn out to be brilliant.