Polygenic Embryo Screening and AI in Reproductive Genomics: Ethics, Law, and Governance at a Critical Juncture

Polygenic embryo screening and AI-assisted embryo assessment are moving from research concept to clinical product faster than the evidence base, regulatory frameworks, or public deliberation can keep pace. Polygenic risk scores are already being marketed to prospective parents for complex traits and diseases, while machine learning tools are reshaping how embryos are evaluated and selected in fertility clinics worldwide. These technologies sit at the intersection of some of the most consequential questions in contemporary science policy: Where does disease prevention end and genetic enhancement begin? Who bears responsibility when algorithmic predictions shape reproductive decisions? And how should societies govern technologies that could deepen or narrow health inequalities across generations?The scientific uncertainties alone are substantial. Polygenic scores explain only a fraction of variation in complex traits, perform unevenly across ancestral populations, and were developed for population-level prediction — not for choosing between sibling embryos. AI-assisted embryo assessment introduces additional concerns around algorithmic bias, opacity, validation, and the outsized influence of commercial providers on clinical adoption and public expectations. Together, these developments challenge established frameworks for informed consent, genetic counselling, disability rights, reproductive autonomy, and equitable access to care.This Research Topic brings together researchers across genetics, bioethics, law, reproductive medicine, social science, AI governance, and public policy to examine how polygenic embryo screening and related reproductive genomic technologies should be evaluated, communicated, regulated, and — where appropriate — constrained. We are building a cross-disciplinary collection designed to inform the policy and clinical guidance conversations that are happening now, in real time, across multiple jurisdictions.We welcome original research, systematic and scoping reviews, policy and practice analyses, perspective pieces, and interdisciplinary legal-ethical-social investigations addressing themes including but not limited to:- Predictive validity, clinical utility, and the communication of uncertainty in polygenic embryo screening- Ancestry-related bias, underrepresentation in reference datasets, and implications for global equity- Transparency, explainability, validation, and accountability in AI-driven embryo assessment- The boundaries between prevention, selection, and enhancement and who draws them- Reproductive autonomy, informed consent, and decision support in the age of algorithmic prediction- Disability rights, eugenics concerns, and the social construction of "healthy" and "normal"- Commercial marketing, direct-to-consumer provision, conflicts of interest, and consumer protection- Equity of access, cost barriers, and the risk of socially stratified reproductive futures- Privacy, data governance, and secondary uses of embryonic and parental genomic data- Comparative regulatory approaches, professional standards, and cross-border reproductive care- Liability frameworks, clinical oversight, and institutional governance of adoption- The perspectives and lived experiences of patients, prospective parents, clinicians, genetic counsellors, disability communities, and affected populationsContributions that bridge disciplinary boundaries are particularly encouraged. Manuscripts focused solely on algorithmic performance metrics, embryo culture protocols, or clinical fertility outcomes without substantive ethical, legal, or social analysis fall outside the scope of this collection. Topic editors: Dov Greenbaum Source: https://www.frontiersin.org/research-topics/85717/polygenic-embryo-screening-and-ai-in-reproductive-genomics-ethics-law-and-governance-at-a-critical-juncture