title: Assessment of the role of genetic polymorphism in venous thrombosis through artificial neural networks.
abstract: OBJECTIVE
  To assess the role of genetic polymorphisms in venous thrombosis events (VTE) using Artificial Neural Networks (ANNs), a model for solving non-linear problems frequently associated with complex biological systems, due to interactions between biological, genetic and environmental factors.
  
  
  METHODS
  A database was generated from a case-control study of venous thrombosis, using 238 patients and 211 controls. The database of 64 variables included age, gender and a panel of 62 genetic variants. Three different ANNs were compared, with logistic regression for the accuracy of predicting cases and controls.
  
  
  RESULTS
  ANNs yielded a better performance than the logistic regression algorithm. Indeed, through ANNs models, the 62 variables related to genetic variants were first reduced to a set of 9, and then of 3 (MTHFR 677 C/T, FV arg506gln, ICAM1 gly214arg).
  
  
  CONCLUSIONS
  The findings of this study illustrate the power of ANN in evaluating multifactorial data, and show that the different sensitivities of the models of elaboration are related to the characteristics of the data. This may contribute to a better understanding of the role played by genetic polymorphisms in VTE, and help to define, if possible, a test panel of genetic variants to estimate an individual's probability of developing the disease.
authors.affiliation: Medical Genetics, Clinical Chemistry and Clinical Pathology Laboratory, Niguarda Ca' Granda Hospital, Piazza Ospedale Maggiore 3, 20100 Milan, Italy. Penco.Silvana@libero.it
authors.forename: S
authors.initials: S
authors.lastname: Penco
authors.forename: E
authors.initials: E
authors.lastname: Grossi
authors.forename: S
authors.initials: S
authors.lastname: Cheng
authors.forename: M
authors.initials: M
authors.lastname: Intraligi
authors.forename: G
authors.initials: G
authors.lastname: Maurelli
authors.forename: M C
authors.initials: MC
authors.lastname: Patrosso
authors.forename: A
authors.initials: A
authors.lastname: Marocchi
authors.forename: M
authors.initials: M
authors.lastname: Buscema
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D016022:Case-Control Studies; D003198:Computer Simulation; D016208:Databases, Factual; D005260:Female; D005796:Genes / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D011110:Polymorphism, Genetic; D020246:Venous Thrombosis / Q000453:epidemiology / Q000235:genetics*