OBJECTIVE: The building of a quantitative relationship between genotype and phenotype would be great helpful for better clinical monitoring, diagnosis, prognosis and treatment. As the phenylketonuria is an autosomal recessive disorder caused by mutations in the phenylalanine hydroxylase, in this study we build a descriptively quantitative relationship between mutant phenylalanine hydroxylase and classifications of phenylketonuria. METHODS: The amino-acid distribution probability is used to quantify the phenylalanine hydroxylase and its mutants, the cross-impact analysis is used to couple mutant phenylalanine hydroxylase and classifications of phenylketonuria, and the Bayesian equation is used to compute the probability that the phenylketonuria can be classified under mutations. RESULTS: The results show that the patient has more than 0.9 chance of being phenylketonuria when a new mutation occurs in phenylalanine hydroxylase. CONCLUSIONS: The built relationship paves the way for modeling of this type relationship for better clinical monitoring, diagnosis, prognosis and treatment.
OBJECTIVE: The building of a quantitative relationship between genotype and phenotype would be great helpful for better clinical monitoring, diagnosis, prognosis and treatment. As the phenylketonuria is an autosomal recessive disorder caused by mutations in the phenylalanine hydroxylase, in this study we build a descriptively quantitative relationship between mutant phenylalanine hydroxylase and classifications of phenylketonuria. METHODS: The amino-acid distribution probability is used to quantify the phenylalanine hydroxylase and its mutants, the cross-impact analysis is used to couple mutant phenylalanine hydroxylase and classifications of phenylketonuria, and the Bayesian equation is used to compute the probability that the phenylketonuria can be classified under mutations. RESULTS: The results show that the patient has more than 0.9 chance of being phenylketonuria when a new mutation occurs in phenylalanine hydroxylase. CONCLUSIONS: The built relationship paves the way for modeling of this type relationship for better clinical monitoring, diagnosis, prognosis and treatment.