Machine learning in prediction of genetic risk of nonsyndromic oral clefts in the Brazilian population.

Objectives: Genetic variants in multiple genes and loci have been associated with the risk of nonsyndromic cleft lip with or without cleft palate (NSCL ± P). However, the estimation of risk remains challenge, because most of these variants are population-specific rendering the identification of the underlying genetic risk difficult. Herein we examined the use of machine learning network in previously reported single nucleotide polymorphisms (SNPs) to predict risk of NSCL ± P in the Brazilian population.

Interactions between superoxide dismutase and paraoxonase polymorphic variants in nonsyndromic cleft lip with or without cleft palate in the Brazilian population.

During development, oxidative stress is hypothesized to mediate embryotoxicity, which may be intensified by exposition to environmental factors and by genetic variations in the enzymes involved in protecting cells from these damaging effects, including superoxide dismutase (SOD) and paraoxonase (PON). The aim of this study was to evaluate the influence of single-nucleotide polymorphisms (SNP) in genes associated with the neutralization of oxidative stress (SOD and PON family members) in the risk of nonsyndromic oral cleft in the Brazilian population. Initially, we tested for association between 28 SNP in SOD1, SOD2, SOD3, PON1, PON2, and PON3 among 325 nonsyndromic cleft lip with or without cleft palate (NSCL±P) case-parent trios.