Browsing by Author "Hipolito, Maria"

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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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    Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder
    (Elsevier, 2019-01-01) Budde, Monika; Friedrichs, Stefanie; Alliey-Rodriguez, Ney; Ament, Seth; Badner, Judith A.; Berrettini, Wade H.; Bloss, Cinnamon S.; Byerley, William; Cichon, Sven; Comes, Ashley L.; Coryell, William; Craig, David W.; Degenhardt, Franziska; Edenberg, Howard J.; Foroud, Tatiana; Forstner, Andreas J.; Frank, Josef; Gershon, Elliot S.; Goes, Fernando S.; Greenwood, Tiffany A.; Guo, Yiran; Hipolito, Maria; Hood, Leroy; Keating, Brendan J.; Koller, Daniel L.; Lawson, William B.; Liu, Chunyu; Mahon, Pamela B.; McInnis, Melvin G.; McMahon, Francis J.; Meier, Sandra M.; Mühleisen, Thomas W.; Murray, Sarah S.; Nievergelt, Caroline M.; Nurnberger, John I.; Nwulia, Evaristus A.; Potash, James B.; Quarless, Danjuma; Rice, John; Roach, Jared C.; Scheftner, William A.; Schork, Nicholas J.; Shekhtman, Tatyana; Shilling, Paul D.; Smith, Erin N.; Streit, Fabian; Strohmaier, Jana; Szelinger, Szabolcs; Treutlein, Jens; Witt, Stephanie H.; Zandi, Peter P.; Zhang, Peng; Zöllner, Sebastian; Bickeböller, Heike; Falkai, Peter G.; Kelsoe, John R.; Nöthen, Markus M.; Rietschel, Marcella; Schulze, Thomas G.; Malzahn, Dörthe; Biochemistry and Molecular Biology, School of Medicine
    Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 – 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 – rs2086256 – rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.