Polygenic Risk Scoring in the Human Embryo: Reproductive Genetics, Final Frontier?

The use of DNA to predict disease and discern risks in advance could lead to substantial improvements in the quality, length, and productivity of human life. We are now on the horizon of applying machine-learning analysis of information from population-wide medical records and genome-wide DNA repositories to reduce the burden of disease in humans. Thousands of publications derived from new resources, such as the Million Veteran Program ( 1 Gaziano J.M. Concato J. Brophy M. Fiore L. Pyarajan S. Breeling J. et al. Million Veteran Program: a mega-biobank to study genetic influences on health and disease. J Clin Epidemiol. 2016; 70: 214-223 Abstract Full Text Full Text PDF PubMed Scopus (292) Google Scholar ) and the UK Biobank ( 2 Sudlow C. Gallacher J. Allen N. Beral V. Burton P. Danesh J. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015; 12e1001779 Crossref PubMed Scopus (2349) Google Scholar ), have led to the development of accurate DNA-based prediction of risk for many human diseases, a concept previously postulated by pioneers in reproductive medicine ( 3 Schulman J.D. Edwards R.G. Preimplantation diagnosis in disease control, not eugenics. Hum Reprod. 1996; 11: 463-464 Crossref PubMed Scopus (16) Google Scholar , 4 Brenner C. Cohen J. The genetic revolution in artificial reproduction: a view of the future. Hum Reprod. 2000; 15: 111-116 Crossref PubMed Scopus (7) Google Scholar , 5 Handyside A.H. Diagnosis of inherited disease before implantation. Reprod Med Rev. 1993; 2: 51-61 Crossref Google Scholar ). Early detection of genetic predisposition to disease was also a goal for pioneers of the Human Genome Project ( 6 Lander E.S. Linton L.M. Birren B. Nusbaum C. Zody M.C. Baldwin J. et al. Initial sequencing and analysis of the human genome. Nature. 2001; 409: 860-921 Crossref PubMed Scopus (16958) Google Scholar ) and International HapMap Project ( 7 The Internation HapMap ConsortiumThe International HapMap Project. Nature. 2003; 426: 789-796 Crossref Scopus (4819) Google Scholar ).