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

Introduction: Congenital anomalies (CA) affects 3-5 % of newborns, representing the second leading cause of infant mortality in Argentina. Newborns presenting multiple congenital anomalies (MCA) have a prevalence of 2,26/1000 births while congenital heart diseases (CHD) are the most frequent CA, with a prevalence of 4,06/1000 births. The goal of this work was to identify the genetic causes in patients with MCA and isolated CHD (iCHD) from Argentina. Material and Methods: We recruited 368 patients (174 MCA and 194 iCHD) born between June 2015 and August 2019 from 13 public hospitals participating in the National Network of Congenital Anomalies of Argentina (RENAC). DNA from peripheral blood was obtained from all patients while karyotyping was performed for those patients presenting with MCA. Samples from patients presenting with conotruncal CHD (cCHD) or DiGeorge phenotype (n=137) were analyzed by MLPA. Ninety-two MCA samples were selected for array-CGH analysis and 18 for targeted or exome next generation sequencing (NGS). Results: A total of 276 patients were studied by at least one technique. Cytogenetic abnormalities were present in 16 MCA patients, while 16 had clinically relevant imbalances detected by array-CGH. Among cCHD patients, 26 presented 22q11 deletions or duplications and one a TBX1 gene deletion. After NGS analysis, 12 patients presented clinically relevant nucleotide variants, 5 of them novels in KAT6B, SHH, MYH11, MYH7 and EP300 genes. Conclusions: Using this algorithm that combines a technical and clinical strategy, 28% of the patients analyzed were diagnosed.