PERSONAL DE APOYO
GIMENEZ lucas Gabriel
congresos y reuniones científicas
Título:
Graph theory as a study means of congenital anomalies associations
Autor/es:
ELIAS, DARIO; CAMPAÑA, HEBE; RITTLER, MONICA; COSENTINO, VIVIANA; SANTOS, RITA; PAWLUK, MARIELA; GIMENEZ, LUCAS; RATOWIECKI, JULIA; POLETTA, FERNANDO; GILI J; LOPEZ CAMELO, JORGE
Lugar:
Bratislava
Reunión:
Conferencia; 46th Annual Meeting of the International Clearinghouse for Birth Defects Surveillance and Research; 2019
Institución organizadora:
International Clearinghouse for Birth Defects Surveillance and Research
Resumen:
Since thalidomide and rubella episodes, surveillance of birth defects has become a public health concern. In order to identify new teratogens, association studies between congenital anomalies have been carried out. To date, two approaches have been conducted to analyze these associations. The former focuses on a specific anomaly and determines the association degree with other anomalies. The latter approach is based on case clustering considering each anomaly as a binary variable. Graph theory may offer another approach. A graph is compound of nodes and edges that represent entities and its relationships respectively. Over the past few years, this approach has enriched many study areas, for example, protein interactions and disease associations. The aim of this study was to evaluate this approach to analyze congenital anomaly associations.We used 170430 cases with at least one anomaly recorded in the Estudio Colaborativo Latino Americano de Malformaciones Congénitas between 1967 and 2017. To determine association strength between anomalies we used volume-adjusted Chi-Squared independence test.The congenital anomalies graph included 98 nodes  (68 major and 30 minor anomalies) and 275 edges. Rectum and anus atresia, Anophthalmia/Microphthalmia and Ambiguous genitalia were the most associated anomalies (> 15). The graph partition had 11 anomaly groups, which would correspond to those found in the literature, such as Patau syndrome. Minor anomalies presented an eigenvector centrality score greater than major anomalies (p-value 0.0018). This suggested that minor anomalies were more associated than major anomalies, and with highly associated anomalies, but this result would be due to the underreporting of minor anomalies.The results suggest that it would be feasible to use the graph theory for congenital anomaly associations study. We believe that this approach would help identify new congenital anomaly complex.