Browsing by Author "Trujillano, Laura"
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Item Clinical relevance of postzygotic mosaicism in Cornelia de Lange syndrome and purifying selection of NIPBL variants in blood.(Scientific Reports, 2021) Latorre Pecillera, Ana; Gil Salvador, Marta; Parenti, Ilaria; Lucía Campos, Cristina; Trujillano, Laura; Marcos Alcalde, Íñigo; Arnedo, María; Ascaso, Ángela; Ayerza‑Casas, Ariadna; Antoñanzas Pérez, Rebeca; Gervasini, Cristina; Piccione, María; Marini, Milena; Weber, Axel; Kuechler, Alma; Bueno‑Lozano, Gloria; Gómez‑Puertas, Paulino; Kaiser, Frank J.; Pié, JuanPostzygotic mosaicism (PZM) in NIPBL is a strong source of causality for Cornelia de Lange syndrome (CdLS) that can have major clinical implications. Here, we further delineate the role of somatic mosaicism in CdLS by describing a series of 11 unreported patients with mosaic disease-causing variants in NIPBL and performing a retrospective cohort study from a Spanish CdLS diagnostic center. By reviewing the literature and combining our findings with previously published data, we demonstrate a negative selection against somatic deleterious NIPBL variants in blood. Furthermore, the analysis of all reported cases indicates an unusual high prevalence of mosaicism in CdLS, occurring in 13.1% of patients with a positive molecular diagnosis. It is worth noting that most of the affected individuals with mosaicism have a clinical phenotype at least as severe as those with constitutive pathogenic variants. However, the type of genetic change does not vary between germline and somatic events and, even in the presence of mosaicism, missense substitutions are located preferentially within the HEAT repeat domain of NIPBL. In conclusion, the high prevalence of mosaicism in CdLS as well as the disparity in tissue distribution provide a novel orientation for the clinical management and genetic counselling of families.Item Evaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes.(International Journal of Molecular Sciences, 2020) Latorre Peciller, Ana; Ascaso, Ángela; Trujillano, Laura; Gil Salvador, Marta; Arnedo, María; Lucía Campos, Cristina; Antoñanzas Pérez, Rebeca; Marcos Alcalde, Íñigo; Parenti, Ilaria; Bueno Lozano, Gloria; Musio, Antonio; Puisac, Beatriz; Kaiser, Frank J.; Ramos, Feliciano J.; Gómez Puertas, Paulino; Pie, JuanCharacteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly di cult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of a ected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to a ect the prediction accuracy, whereas our results indicate a correlation between the clinical score and a ected genes. Furthermore, each gene presents a di erent pattern recognition that may be used to develop new neural networks with the goal of separating di erent genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdLS.