Polygenic risk scores (PRSs) have been offered since 2019 to screen in vitro fertilization embryos for genetic liability to adult diseases, despite a lack of comprehensive modeling of expected outcomes. Here we predict, based on the liability threshold model, the expected reduction in complex disease risk following polygenic embryo screening for a single disease. A strong determinant of the potential utility of such screening is the selection strategy, a factor that has not been previously studied. When only embryos with a very high PRS are excluded, the achieved risk reduction is minimal. In contrast, selecting the embryo with the lowest PRS can lead to substantial relative risk reductions, given a sufficient number of viable embryos. We systematically examine the impact of several factors on the utility of screening, including: variance explained by the PRS, number of embryos, disease prevalence, parental PRSs, and parental disease status. We consider both relative and absolute risk reductions, as well as population-averaged and per-couple risk reductions, and also examine the risk of pleiotropic effects. Finally, we confirm our theoretical predictions by simulating 'virtual' couples and offspring based on real genomes from schizophrenia and Crohn's disease case-control studies. We discuss the assumptions and limitations of our model, as well as the potential emerging ethical concerns.
It has become increasingly apparent that the trophectoderm (TE) at blastocyst stage is much more mosaic than has been appreciated. Whether preimplantation genetic screening (PGS), utilizing a single TE biopsy (TEB), can reliably determine embryo ploidy has, therefore, increasingly been questioned in parallel. We for that reason here established 2 mathematical models to assess probabilities of false-negative and false-positive results of an on average 6-cell biopsy from an approximately 300-cell TE. This study was a collaborative effort between investigators at The Center for Human Reproduction in New York City and the Center for Studies in Physics and Biology and the Brivanlou Laboratory of Stem Cell Biology and Molecular Embryology, the latter two both at Rockefeller University in New York City. Both models revealed that even under best case scenario, assuming even distribution of mosaicism in TE (since mosaicism is usually clonal, a highly unlikely scenario), a biopsy of at least 27 TE cells would be required to reach minimal diagnostic predictability from a single TEB. As currently performed, a single TEB is, therefore, mathematically incapable of reliably determining whether an embryo can be transferred or should be discarded. Since a single TEB, as currently performed, apparently is not representative of the complete TE, this study, thus, raises additional concern about the clinical utilization of PGS.
Preimplantation genetic testing for polygenic disorders (PGT-P) has been commercially available since 2019. PGT-P makes use of polygenic risk scores for conditions which are multifactorial and are significantly influenced by environmental and lifestyle factors. If current predictions are accurate, then absolute risk reductions range from about 0.02% to 10.1%, meaning that between 10 and 5,000 in vitro fertilization patients would need to be tested with PGT-P to prevent one offspring from becoming affected in the future, depending on the condition and the number of embryos available. Survey and interview data reveal that patients and the public have largely favorable views regarding the use of PGT-P for disease prevention; however, clinicians and professional organizations have many reservations. The use of PGT-P raises multiple social and ethical concerns including the need for adequate counseling, the setting of realistic expectations, the application of distributive justice, the impact of environmental and social determinants of health, and the potential exacerbation of health inequities. Clinicians expressed significant concerns relating to the cost of PGT-P, the potential time-consuming counseling for reproductive endocrinologists and genetic counselors, the intentional creation of supernumerary embryos, and patients' unrealistic expectations regarding "healthiest disease-free" embryos. Furthermore, current evidence lacks long-term outcome data and generalizability. Prior to offering PGT-P to patients, additional clinical validation studies are needed. Also, ethical and social considerations raised by PGT-P should be carefully delineated. Systemic practices to increase equitable access to unbiased genetic counseling and reproductive services would be desirable prior to the ethical implementation of PGT-P.
Practice Committees of the American Society for Reproductive Medicine and the Society for Assisted Reproductive Technology, 2024·Fertil Steril
The use of preimplantation genetic testing for aneuploidy (PGT-A) in the United States has been increasing steadily. Moreover, the underlying technology used for 24-chromosome analysis continues to evolve rapidly. The value of PGT-A as a routine screening test for all patients undergoing in vitro fertilization has not been demonstrated. Although some earlier single-center studies reported higher live-birth rates after PGT-A in favorable-prognosis patients, recent multicenter, randomized control trials in women with available blastocysts concluded that the overall pregnancy outcomes via frozen embryo transfer were similar between PGT-A and conventional in vitro fertilization. The value of PGT-A to lower the risk of clinical miscarriage is also unclear, although these studies have important limitations. This document replaces the document of the same name, last published in 2018.
gynecology/pelvic-pain/chronic-pelvic-painendometriosis/diagnosis/diagnostic-delayresearch-methods/measurement-and-statistics/statistical-methods
Open Access
Endometriosis is a debilitating, chronic disease that is estimated to affect 11% of reproductive-age women. Diagnosis of endometriosis is difficult with diagnostic delays of up to 12 years reported. These delays can negatively impact health and quality of life. Vague, nonspecific symptoms, like pain, with multiple differential diagnoses contribute to the difficulty of diagnosis. By investigating previously imprecise symptoms of pain, we sought to clarify distinct pain symptoms indicative of endometriosis, using an artificial intelligence-based approach. We used data from 473 women undergoing laparoscopy or laparotomy for a variety of surgical indications. Multiple anatomical pain locations were clustered based on the associations across samples to increase the power in the probability calculations. A Bayesian network was developed using pain-related features, subfertility, and diagnoses. Univariable and multivariable analyses were performed by querying the network for the relative risk of a postoperative diagnosis, given the presence of different symptoms. Performance and sensitivity analyses demonstrated the advantages of Bayesian network analysis over traditional statistical techniques. Clustering grouped the 155 anatomical sites of pain into 15 pain locations. After pruning, the final Bayesian network included 18 nodes. The presence of any pain-related feature increased the relative risk of endometriosis (p-value < 0.001). The constellation of chronic pelvic pain, subfertility, and dyspareunia resulted in the greatest increase in the relative risk of endometriosis. The performance and sensitivity analyses demonstrated that the Bayesian network could identify and analyze more significant associations with endometriosis than traditional statistical techniques. Pelvic pain, frequently associated with endometriosis, is a common and vague symptom. Our Bayesian network for the study of pain-related features of endometriosis revealed specific pain locations and pain types that potentially forecast the diagnosis of endometriosis.