Abstract
BackgroundThe increasing number of available genotypes for genetic studies in humans requires more advanced techniques of analysis. We previously reported significant univariate associations between gene polymorphisms and antidepressant response in mood disorders. However the combined analysis of multiple gene polymorphisms and clinical variables requires the use of non linear methods.MethodsIn the present study we tested a neural network strategy for a combined analysis of two gene polymorphisms. A Multi Layer Perceptron model showed the best performance and was therefore selected over the other networks. One hundred and twenty one depressed inpatients treated with fluvoxamine in the context of previously reported pharmacogenetic studies were included. The polymorphism in the transcriptional control region upstream of the 5HTT coding sequence (SERTPR) and in the Tryptophan Hydroxylase (TPH) gene were analysed simultaneously.ResultsA multi layer perceptron network composed by 1 hidden layer with 7 nodes was chosen. 77.5 % of responders and 51.2% of non responders were correctly classified (ROC area = 0.731 – empirical p value = 0.0082). Finally, we performed a comparison with traditional techniques. A discriminant function analysis correctly classified 34.1 % of responders and 68.1 % of non responders (F = 8.16 p = 0.0005).ConclusionsOverall, our findings suggest that neural networks may be a valid technique for the analysis of gene polymorphisms in pharmacogenetic studies. The complex interactions modelled through NN may be eventually applied at the clinical level for the individualized therapy.
Highlights
IntroductionThe combined analysis of multiple gene polymorphisms and clinical variables requires the use of non linear methods
The increasing number of available genotypes for genetic studies in humans requires more advanced techniques of analysis
Nine patients with extreme plasma levels were removed from the study in order to avoid biases due to side effects that are present at high doses, subjects with plasma levels below 20 ng/ml were excluded as this may indicate non compliance, but no cases with such low doses were observed. The influence of both SERTPR and Tryptophan Hydroxylase (TPH) polymorphisms was limited to subjects not taking pindolol [32] we included in the present study the 121 subjects including fluvoxamine alone (81 responders/40 non responders)
Summary
The combined analysis of multiple gene polymorphisms and clinical variables requires the use of non linear methods. The increasing number of available genotypes for genetic studies in humans requires more advanced techniques of analysis [1]. Traditional statistical techniques are not appropriate for detecting such effects [4], because they rely on the basic assumption of linear combinations only [5]. Investigation in multifactorial disorders evidenced that non linear interactions are not detected by traditional regression analyses [6]. Psychiatric disorders are characterized by a non mendelian, multifactorial genetic contribution with a number of susceptibility genes interacting with each other [7,8]. In the process of disentangling the contribution of environment versus genes, it has been recently suggested (page number not for citation purposes)
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