Genetic Analysis Algorithm for the Study of Patients with Multiple Congenital Anomalies and Isolated Congenital Heart Disease

Genetic Analysis Algorithm for the Study of Patients with Multiple Congenital Anomalies and Isolated Congenital Heart Disease

Congenital anomalies (CA) affect 3–5% of newborns, representing the second-leading cause of infant mortality in Argentina. Multiple congenital anomalies (MCA) have a prevalence of 2.26/1000 births in newborns, while congenital heart diseases (CHD) are the most frequent CA with a prevalence of 4.06/1...

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Bibliographic Details
Main Authors: Marisol Delea, Lucia S. Massara, Lucia D. Espeche, María Paz Bidondo, Pablo Barbero, Jaen Oliveri, Paloma Brun, Mónica Fabro, Micaela Galain, Cecilia S. Fernández, Melisa Taboas, Carlos D. Bruque, Jorge E. Kolomenski, Agustín Izquierdo, Ariel Berenstein, Viviana Cosentino, Celeste Martinoli, Mariana Vilas, Mónica Rittler, Rodrigo Mendez, Lilian Furforo, Rosa Liascovich, Boris Groisman, Sandra Rozental, Liliana Dain, on behalf of the PID ACM-CC Group
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Genes
Subjects:
multiple congenital anomalies
congenital heart disease
chromosomal abnormalities
array-CGH
next-generation sequencing
Online Access:https://www.mdpi.com/2073-4425/13/7/1172

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https://www.mdpi.com/2073-4425/13/7/1172

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