Background. High-quality clinical and genetic descriptions are crucial to improve knowledge of orofacial clefts and support specific healthcare polices. The objective of this study is to discuss the potential and perspectives of the Brazilian Database on Orofacial Clefts. Methods. From 2008 to 2010, clinical and familial information on 370 subjects was collected by geneticists in eight different services. Data was centrally processed using an international system for case classification and coding. Results. Cleft lip with cleft palate amounted to 198 (53.5%), cleft palate to 99 (26.8%), and cleft lip to 73 (19.7%) cases. Parental consanguinity was present in 5.7% and familial history of cleft was present in 26.3% subjects. Rate of associated major plus minor defects was 48% and syndromic cases amounted to 25% of the samples. Conclusions. Overall results corroborate the literature. Adopted tools are user friendly and could be incorporated into routine patient care. The BDOC exemplifies a network for clinical and genetic research. The data may be useful to develop and improve personalized treatment, family planning, and healthcare policies. This experience should be of interest for geneticists, laboratory-based researchers, and clinicians entrusted with OC worldwide. 1. Introduction Accurate and detailed phenotype description of orofacial clefts (OC) is crucial to produce good etiological and epidemiological studies. In this regard, attention should be given to subphenotypic features of the lip (completeness of the cleft, presence of pits/prints, dental and orbicularis oris muscle anomalies), and palate (completeness of the cleft, submucous defects, bifid uvula, and ankyloglossia). Similarly important is the screening of minor and major associated defects which has prevalence rate that ranges from 8% to 75%. Although there are true population differences, methodological factors such as sample source and size, method of ascertainment, case definitions, inclusion criteria, coding system, and case classification account for much of this wide variation [1–13]. In the postgenomic era capturing and processing information on human genetic variation, gene-environment interactions, and genotype-phenotype correlations are essential to develop personalized interventions. This has been reinforced by the Human Variome Project (HVP), an international effort launched in 2006. The HVP aim is to develop and make knowledge housed within linked databases on genes, mutations, and variants accessible to the research and medical communities [14, 15]. Databases may also serve
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