Prenatal exome sequencing, a powerful tool for improving the description of prenatal features associated with genetic disorders

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Thauvin-Robinet, Christel | Garde, Aurore | Delanne, Julian | Racine, Caroline | Rousseau, Thierry | Simon, Emmanuel | François, Michel | Moutton, Sebastien | Sylvie, Odent | Quelin, Chloe | Morel, Godelieve | Goldenberg, Alice | Guerrot, Anne‐marie | Vera, Gabriella | Gruchy, Nicolas | Colson, Cindy | Boute, Odile | Abel, Carine | Putoux, Audrey | Amiel, Jeanne | Guichet, Agnes | Isidor, Bertrand | Deiller, Caroline | Wells, Constance | Rooryck, Caroline | Legendre, Marine | Francannet, Christine | Dard, Rodolphe | Sigaudy, Sabine | Bruel, Ange‐line | Safraou, Hana | Denommé-Pichon, Anne‐sophie | Nambot, Sophie | Asensio, Marie‐laure Humbert | Binquet, Christine | Duffourd, Yannis | Vitobello, Antonio | Philippe, Christophe | Faivre, Laurence | Tran-Mau-Them, Frédéric | Bourgon, Nicolas

Edité par CCSD ; Wiley -

International audience. Abstract Objective Prenatal exome sequencing (pES) is now commonly used in clinical practice. It can be used to identifiy an additional diagnosis in around 30% of fetuses with structural defects and normal chromosomal microarray analysis (CMA). However, interpretation remains challenging due to the limited prenatal data for genetic disorders. Method We conducted an ancillary study including fetuses with pathogenic/likely pathogenic variants identified by trio‐pES from the “AnDDI‐Prenatome” study. The prenatal phenotype of each patient was categorized as typical, uncommon, or unreported based on the comparison of the prenatal findings with documented findings in the literature and public phenotype‐genotype databases (ClinVar, HGMD, OMIM, and Decipher). Results Prenatal phenotypes were typical for 38/56 fetuses (67.9%). For the others, genotype‐phenotype associations were challenging due to uncommon prenatal features (absence of recurrent hallmark, rare, or unreported). We report the first prenatal features associated with LINS1 and PGM1 variants. In addition, a double diagnosis was identified in three fetuses. Conclusion Standardizing the description of prenatal features, implementing longitudinal prenatal follow‐up, and large‐scale collection of prenatal features are essential steps to improving pES data interpretation.

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