title: Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data.
abstract: BACKGROUND
  Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets.
  
  
  RESULTS
  The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals.
  
  
  CONCLUSIONS
  Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data.
  
  
  BACKGROUND
  http://sourceforge.net/projects/sdrproject/.
authors.affiliation: Referral Center for Systemic Autoimmune Diseases, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico and University of Milan, Milan, Italy. lorberimm@hotmail.com
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Beretta
authors.forename: Alessandro
authors.initials: A
authors.lastname: Santaniello
authors.forename: Piet L C M
authors.initials: PL
authors.lastname: van Riel
authors.forename: Marieke J H
authors.initials: MJ
authors.lastname: Coenen
authors.forename: Raffaella
authors.initials: R
authors.lastname: Scorza
mesh_terms: D000328:Adult; D000465:Algorithms; D018501:Antirheumatic Agents / Q000627:therapeutic use; D001172:Arthritis, Rheumatoid / Q000188:drug therapy* / Q000235:genetics*; D016022:Case-Control Studies; D003198:Computer Simulation; D004843:Epistasis, Genetic; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D014409:Tumor Necrosis Factor-alpha / Q000037:antagonists & inhibitors
chemical_list: D018501:Antirheumatic Agents; D014409:Tumor Necrosis Factor-alpha