TY  - JOUR
A1  - Davis, Lea K.
A1  - Yu, Dongmei
A1  - Keenan, Clare L.
A1  - Gamazon, Eric R.
A1  - Konkashbaev, Anuar I.
A1  - Derks, Eske M.
A1  - Neale, Benjamin M.
A1  - Yang, Jian
A1  - Lee, S. Hong
A1  - Evans, Patrick
A1  - Barr, Cathy L.
A1  - Bellodi, Laura
A1  - Benarroch, Fortu
A1  - Berrio, Gabriel Bedoya
A1  - Bienvenu, Oscar J.
A1  - Bloch, Michael H.
A1  - Blom, Rianne M.
A1  - Bruun, Ruth D.
A1  - Budman, Cathy L.
A1  - Camarena, Beatriz
A1  - Campbell, Desmond
A1  - Cappi, Carolina
A1  - Cardona Silgado, Julio C.
A1  - Cath, Danielle C.
A1  - Cavallini, Maria C.
A1  - Chavira, Denise A.
A1  - Chouinard, Sylvian
A1  - Conti, David V.
A1  - Cook, Edwin H.
A1  - Coric, Vladimir
A1  - Cullen, Bernadette A.
A1  - Deforce, Dieter
A1  - Delorme, Richard
A1  - Dion, Yves
A1  - Edlund, Christopher K.
A1  - Egberts, Karin
A1  - Falkai, Peter
A1  - Fernandez, Thomas V.
A1  - Gallagher, Patience J.
A1  - Garrido, Helena
A1  - Geller, Daniel
A1  - Girard, Simon L.
A1  - Grabe, Hans J.
A1  - Grados, Marco A.
A1  - Greenberg, Benjamin D.
A1  - Gross-Tsur, Varda
A1  - Haddad, Stephen
A1  - Heiman, Gary A.
A1  - Hemmings, Sian M. J.
A1  - Hounie, Ana G.
A1  - Illmann, Cornelia
A1  - Jankovic, Joseph
A1  - Jenike, Micheal A.
A1  - Kennedy, James L.
A1  - King, Robert A.
A1  - Kremeyer, Barbara
A1  - Kurlan, Roger
A1  - Lanzagorta, Nuria
A1  - Leboyer, Marion
A1  - Leckman, James F.
A1  - Lennertz, Leonhard
A1  - Liu, Chunyu
A1  - Lochner, Christine
A1  - Lowe, Thomas L.
A1  - Macciardi, Fabio
A1  - McCracken, James T.
A1  - McGrath, Lauren M.
A1  - Restrepo, Sandra C. Mesa
A1  - Moessner, Rainald
A1  - Morgan, Jubel
A1  - Muller, Heike
A1  - Murphy, Dennis L.
A1  - Naarden, Allan L.
A1  - Ochoa, William Cornejo
A1  - Ophoff, Roel A.
A1  - Osiecki, Lisa
A1  - Pakstis, Andrew J.
A1  - Pato, Michele T.
A1  - Pato, Carlos N.
A1  - Piacentini, John
A1  - Pittenger, Christopher
A1  - Pollak, Yehunda
A1  - Rauch, Scott L.
A1  - Renner, Tobias J.
A1  - Reus, Victor I.
A1  - Richter, Margaret A.
A1  - Riddle, Mark A.
A1  - Robertson, Mary M.
A1  - Romero, Roxana
A1  - Rosàrio, Maria C.
A1  - Rosenberg, David
A1  - Rouleau, Guy A.
A1  - Ruhrmann, Stephan
A1  - Ruiz-Linares, Andreas
A1  - Sampaio, Aline S.
A1  - Samuels, Jack
A1  - Sandor, Paul
A1  - Sheppard, Broke
A1  - Singer, Harvey S.
A1  - Smit, Jan H.
A1  - Stein, Dan J.
A1  - Strengman, E.
A1  - Tischfield, Jay A.
A1  - Valencia Duarte, Ana V.
A1  - Vallada, Homero
A1  - Van Nieuwerburgh, Flip
A1  - Veenstra-VanderWeele, Jeremy
A1  - Walitza, Susanne
A1  - Wang, Ying
A1  - Wendland, Jens R.
A1  - Westenberg, Herman G. M.
A1  - Shugart, Yin Yao
A1  - Miguel, Euripedes C.
A1  - McMahon, William
A1  - Wagner, Michael
A1  - Nicolini, Humberto
A1  - Posthuma, Danielle
A1  - Hanna, Gregory L.
A1  - Heutink, Peter
A1  - Denys, Damiaan
A1  - Arnold, Paul D.
A1  - Oostra, Ben A.
A1  - Nestadt, Gerald
A1  - Freimer, Nelson B.
A1  - Pauls, David L.
A1  - Wray, Naomi R.
A1  - Stewart, S. Evelyn
A1  - Mathews, Carol A.
A1  - Knowles, James A.
A1  - Cox, Nancy J.
A1  - Scharf, Jeremiah M.
T1  - Partitioning the Heritability of Tourette Syndrome and Obsessive Compulsive Disorder Reveals Differences in Genetic Architecture
JF  - PLoS Genetics
N2  - The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained by all SNPs for two phenotypically-related neurobehavioral disorders, obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS), using GCTA. Our analysis yielded a heritability point estimate of 0.58 (se = 0.09, p = 5.64e-12) for TS, and 0.37 (se = 0.07, p = 1.5e-07) for OCD. In addition, we conducted multiple genomic partitioning analyses to identify genomic elements that concentrate this heritability. We examined genomic architectures of TS and OCD by chromosome, MAF bin, and functional annotations. In addition, we assessed heritability for early onset and adult onset OCD. Among other notable results, we found that SNPs with a minor allele frequency of less than 5% accounted for 21% of the TS heritability and 0% of the OCD heritability. Additionally, we identified a significant contribution to TS and OCD heritability by variants significantly associated with gene expression in two regions of the brain (parietal cortex and cerebellum) for which we had available expression quantitative trait loci (eQTLs). Finally we analyzed the genetic correlation between TS and OCD, revealing a genetic correlation of 0.41 (se = 0.15, p = 0.002). These results are very close to previous heritability estimates for TS and OCD based on twin and family studies, suggesting that very little, if any, heritability is truly missing (i.e., unassayed) from TS and OCD GWAS studies of common variation. The results also indicate that there is some genetic overlap between these two phenotypically-related neuropsychiatric disorders, but suggest that the two disorders have distinct genetic architectures.
KW  - TIC disorders
KW  - missing heritability
KW  - complex diseases
KW  - neuropsychiatric disorders
KW  - common SNPS
KW  - gilles
KW  - family
KW  - brain
KW  - expression
KW  - autism
Y1  - 2013
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-127377
SN  - 1553-7390
VL  - 9
IS  - 10
ER  - 
TY  - JOUR
A1  - Breuer, René
A1  - Mattheisen, Manuel
A1  - Frank, Josef
A1  - Krumm, Bertram
A1  - Treutlein, Jens
A1  - Kassem, Layla
A1  - Strohmaier, Jana
A1  - Herms, Stefan
A1  - Mühleisen, Thomas W.
A1  - Degenhardt, Franziska
A1  - Cichon, Sven
A1  - Nöthen, Markus M.
A1  - Karypis, George
A1  - Kelsoe, John
A1  - Greenwood, Tiffany
A1  - Nievergelt, Caroline
A1  - Shilling, Paul
A1  - Shekhtman, Tatyana
A1  - Edenberg, Howard
A1  - Craig, David
A1  - Szelinger, Szabolcs
A1  - Nurnberger, John
A1  - Gershon, Elliot
A1  - Alliey-Rodriguez, Ney
A1  - Zandi, Peter
A1  - Goes, Fernando
A1  - Schork, Nicholas
A1  - Smith, Erin
A1  - Koller, Daniel
A1  - Zhang, Peng
A1  - Badner, Judith
A1  - Berrettini, Wade
A1  - Bloss, Cinnamon
A1  - Byerley, William
A1  - Coryell, William
A1  - Foroud, Tatiana
A1  - Guo, Yirin
A1  - Hipolito, Maria
A1  - Keating, Brendan
A1  - Lawson, William
A1  - Liu, Chunyu
A1  - Mahon, Pamela
A1  - McInnis, Melvin
A1  - Murray, Sarah
A1  - Nwulia, Evaristus
A1  - Potash, James
A1  - Rice, John
A1  - Scheftner, William
A1  - Zöllner, Sebastian
A1  - McMahon, Francis J.
A1  - Rietschel, Marcella
A1  - Schulze, Thomas G.
T1  - Detecting significant genotype–phenotype association rules in bipolar disorder: market research meets complex genetics
JF  - International Journal of Bipolar Disorders
N2  - 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.
KW  - bipolar disorder
KW  - subphenotypes
KW  - rule discovery
KW  - data mining
KW  - genotype-phenotype patterns
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-220509
VL  - 6
ER  -