Molecular Genetics and Reproductive Genomic Medicine in Cleft Lip and Palate: Current Evidence, Preimplantation Testing, and Clinical Translation—A Narrative Review

Cleft lip and palate (CLP) is a common congenital craniofacial anomaly with heterogeneous clinical manifestations and complex etiologies. Current evidence indicates that CLP arises from the combined effects of Mendelian syndromic disorders, rare pathogenic variants, common susceptibility loci, non-coding regulatory variants, epigenetic regulation, mitochondrial dysfunction, and maternal environmental exposures. Although reconstructive surgery and multidisciplinary care remain central to treatment, families with recurrent CLP or a family history of orofacial clefts increasingly seek reproductive counseling and genetic risk assessment before pregnancy. Preimplantation genetic testing (PGT) may provide a clinically meaningful option when a pathogenic variant, chromosomal abnormality, or clearly defined familial haplotype is identified. However, most non-syndromic CLP cases are polygenic or multifactorial, and the application of preimplantation genetic testing for polygenic disorders (PGT-P) remains limited by modest predictive accuracy, population-specific transferability, embryo-number constraints, incomplete penetrance, variants of uncertain significance, and uncertain long-term clinical utility. This narrative review summarizes the clinical phenotypes and genomic architecture of CLP, evaluates the principles and current limitations of preimplantation genetic testing for monogenic disorders (PGT-M) and PGT-P, and discusses psychosocial and ethical issues in reproductive decision-making. We propose that PGT for CLP should be positioned as part of a stepwise counseling framework rather than as a universal preventive strategy. Future progress will depend on standardized phenotyping, multi-ancestry genomic databases, functional validation of candidate variants, transparent risk communication, and shared decision-making that respects both reproductive autonomy and the uncertainty of genomic prediction.