Browsing by Author "Scheftner, William"

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    Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics
    (SpringerOpen, 2018-11-11) 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.; Biochemistry and Molecular Biology, School of Medicine
    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.
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    Familial aggregation of postpartum mood symptoms in bipolar disorder pedigrees
    (Wiley, 2008-02) Payne, Jennifer L; MacKinnon, Dean F.; Mondimore, Francis M.; McInnis, Melvin G.; Schweizer, Barbara; Zamoiski, Rachel B.; McMahon, Francis J.; Nurnberger, John I., Jr.; Rice, John P.; Scheftner, William; Coryell, William; Berrettini, Wade H.; Kelsoe, John R.; Byerley, William; Gershon, Elliot S.; DePaulo, J. Raymond, Jr.; Potash, James B.; Medicine, School of Medicine
    OBJECTIVES: We sought to determine if postpartum mood symptoms and depressive episodes exhibit familial aggregation in bipolar I pedigrees. METHODS: A total of 1,130 women were interviewed with the Diagnostic Interview for Genetic Studies as part of the National Institute of Mental Health (NIMH) Genetics Initiative Bipolar Disorder Collaborative Study and were asked whether they had ever experienced mood symptoms within four weeks postpartum. Women were also asked whether either of two major depressive episodes described in detail occurred postpartum. We examined the odds of postpartum mood symptoms in female siblings, who had previously been pregnant and had a diagnosis of bipolar I, bipolar II, or schizoaffective (bipolar type) disorders (n = 303), given one or more relatives with postpartum mood symptoms. RESULTS: The odds ratio for familial aggregation of postpartum mood symptoms was 2.31 (p = 0.011) in an Any Mood Symptoms analysis (n = 304) and increased to 2.71 (p = 0.005) when manic symptoms were excluded, though this was not significantly different from the Any Mood Symptoms analysis. We also examined familial aggregation of postpartum major depressive episodes; however, the number of subjects was small. CONCLUSIONS: Limitations of the study include the retrospective interview, the fact that the data were collected for other purposes and the inability to control for such factors as medication use. Taken together with previous studies, these data provide support for the hypothesis that there may be a genetic basis for the trait of postpartum mood symptoms generally and postpartum depressive symptoms in particular in women with bipolar disorder. Genetic linkage and association studies incorporating this trait are warranted.