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Prediction of serotonin transporter promoter polymorphism genotypes from single nucleotide polymorphism arrays using machine learning methods.

Filed under Diagnostics, Genotyping, Health no comments

Prediction of serotonin transporter promoter polymorphism genotypes from single nucleotide polymorphism arrays using machine learning methods.

Psychiatr Genet. 2012 Apr 11;

Authors: Lu AT, Bakker S, Janson E, Cichon S, Cantor RM, Ophoff RA

Abstract
BACKGROUND: The serotonin transporter gene (SLC6A4) and its promoter (5-HTTLPR) polymorphism have been the focus of a large number of association studies of behavioral traits and psychiatric disorders. However, large-scale genotyping of the polymorphism has been very difficult. We report the development and validation of a 5-HTTLPR genotype prediction model. METHODS: The single nucleotide polymorphisms (SNPs) from the 2000 kb region surrounding 5-HTTLPR were used to construct a prediction model through a newly developed machine learning method, multicategory vertex discriminant analysis with 2147 individuals from the Northern Finnish Birth Cohort genotyped with the Illumina 370K SNP array and manually genotyped for 5-HTTLPR polymorphism. The prediction model was applied to SNP genotypes in a Dutch/German schizophrenia case-control sample of 3318 individuals to test the association of the polymorphism with schizophrenia. RESULT: The prediction model of eight SNPs achieved a 92.4% accuracy rate and a 0.98±0.01 area under the receiving operating characteristic. Evidence for an association of the polymorphism with schizophrenia was observed (P=0.05, odds ratio=1.105). CONCLUSION: This prediction model provides an effective substitute of manually genotyped 5-HTTLPR alleles, providing a new approach for large scale association studies of this polymorphism.

PMID: 22504458 [PubMed - as supplied by publisher]

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