title: Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics
creator: Breuer, René
creator: Mattheisen, Manuel
creator: Frank, Josef
creator: Krumm, Bertram
creator: Treutlein, Jens
creator: Kassem, Layla
creator: Strohmaier, Jana
creator: Herms, Stefan
creator: Mühleisen, Thomas W.
creator: Degenhardt, Franziska
creator: Cichon, Sven
creator: Nöthen, Markus M.
creator: Karypis, George
creator: Kelsoe, John
creator: Greenwood, Tiffany
creator: Nievergelt, Caroline
creator: Shilling, Paul
creator: Shekhtman, Tatyana
creator: Edenberg, Howard
creator: Craig, David
creator: Szelinger, Szabolcs
creator: Nurnberger, John
creator: Gershon, Elliot
creator: Alliey-Rodriguez, Ney
creator: Zandi, Peter
creator: Goes, Fernando
creator: Schork, Nicholas
creator: Smith, Erin
creator: Koller, Daniel
creator: Zhang, Peng
creator: Badner, Judith
creator: Berrettini, Wade
creator: Bloss, Cinnamon
creator: Byerley, William
creator: Coryell, William
creator: Foroud, Tatiana
creator: Guo, Yirin
creator: Hipolito, Maria
creator: Keating, Brendan
creator: Lawson, William
creator: Liu, Chunyu
creator: Mahon, Pamela
creator: McInnis, Melvin
creator: Murray, Sarah
creator: Nwulia, Evaristus
creator: Potash, James
creator: Rice, John
creator: Scheftner, William
creator: Zöllner, Sebastian
creator: McMahon, Francis J.
creator: Rietschel, Marcella
creator: Schulze, Thomas G.
subject: ddc-610
subject: 610 Medical sciences Medicine
description: Background: Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype–phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted.    Results: Two of these rules—one associated with eating disorder and the other with anxiety—remained significant in an independent dataset after robust correction for multiple testing. Both showed considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively) and support previously reported molecular biological findings.    Conclusion: Our approach detected novel specific genotype–phenotype relationships in BD that were missed by standard analyses like GWAS. While we developed and applied our method within the context of BD gene discovery, it may facilitate identifying highly specific genotype–phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts.
publisher: Springer
date: 2018-11
type: Article
type: info:eu-repo/semantics/article
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/25599/1/40345_2018_Article_132.pdf
identifier: DOI:
identifier: urn:nbn:de:bsz:16-heidok-255992
identifier:   Breuer, René ; Mattheisen, Manuel ; Frank, Josef ; Krumm, Bertram ; Treutlein, Jens ; Kassem, Layla ; Strohmaier, Jana ; Herms, Stefan ; Mühleisen, Thomas W. ; Degenhardt, Franziska ; Cichon, Sven ; Nöthen, Markus M. ; Karypis, George ; Kelsoe, John ; Greenwood, Tiffany ; Nievergelt, Caroline ; Shilling, Paul ; Shekhtman, Tatyana ; Edenberg, Howard ; Craig, David ; Szelinger, Szabolcs ; Nurnberger, John ; Gershon, Elliot ; Alliey-Rodriguez, Ney ; Zandi, Peter ; Goes, Fernando ; Schork, Nicholas ; Smith, Erin ; Koller, Daniel ; Zhang, Peng ; Badner, Judith ; Berrettini, Wade ; Bloss, Cinnamon ; Byerley, William ; Coryell, William ; Foroud, Tatiana ; Guo, Yirin ; Hipolito, Maria ; Keating, Brendan ; Lawson, William ; Liu, Chunyu ; Mahon, Pamela ; McInnis, Melvin ; Murray, Sarah ; Nwulia, Evaristus ; Potash, James ; Rice, John ; Scheftner, William ; Zöllner, Sebastian ; McMahon, Francis J. ; Rietschel, Marcella ; Schulze, Thomas G.  (2018) Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics.  International Journal of Bipolar Disorders, 6 (24).  pp. 1-10.  ISSN 2194-7511     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/25599/
rights: info:eu-repo/semantics/openAccess
rights: Please see front page of the work (Sorry, Dublin Core plugin does not recognise license id)
language: eng