TY  - JOUR
A1  - Manchia, Mirko
A1  - Adli, Mazda
A1  - Akula, Nirmala
A1  - Arda, Raffaella
A1  - Aubry, Jean-Michel
A1  - Backlund, Lena
A1  - Banzato, Claudio E. M.
A1  - Baune, Bernhard T.
A1  - Bellivier, Frank
A1  - Bengesser, Susanne
A1  - Biernacka, Joanna M.
A1  - Brichant-Petitjean, Clara
A1  - Bui, Elise
A1  - Calkin, Cynthia V.
A1  - Cheng, Andrew Tai Ann
A1  - Chillotti, Caterina
A1  - Cichon, Sven
A1  - Clark, Scott
A1  - Czerski, Piotr M.
A1  - Dantas, Clarissa
A1  - Del Zompo, Maria
A1  - DePaulo, J. Raymond
A1  - Detera-Wadleigh, Sevilla D.
A1  - Etain, Bruno
A1  - Falkai, Peter
A1  - Frisén, Louise
A1  - Frye, Mark A.
A1  - Fullerton, Jan
A1  - Gard, Sébastien
A1  - Garnham, Julie
A1  - Goes, Fernando S.
A1  - Grof, Paul
A1  - Gruber, Oliver
A1  - Hashimoto, Ryota
A1  - Hauser, Joanna
A1  - Heilbronner, Urs
A1  - Hoban, Rebecca
A1  - Hou, Liping
A1  - Jamain, Stéphane
A1  - Kahn, Jean-Pierre
A1  - Kassem, Layla
A1  - Kato, Tadafumi
A1  - Kelsoe, John R.
A1  - Kittel-Schneider, Sarah
A1  - Kliwicki, Sebastian
A1  - Kuo, Po-Hsiu
A1  - Kusumi, Ichiro
A1  - Laje, Gonzalo
A1  - Lavebratt, Catharina
A1  - Leboyer, Marion
A1  - Leckband, Susan G.
A1  - López Jaramillo, Carlos A.
A1  - Maj, Mario
A1  - Malafosse, Alain
A1  - Martinsson, Lina
A1  - Masui, Takuya
A1  - Mitchell, Philip B.
A1  - Mondimore, Frank
A1  - Monteleone, Palmiero
A1  - Nallet, Audrey
A1  - Neuner, Maria
A1  - Novák, Tomás
A1  - O'Donovan, Claire
A1  - Ösby, Urban
A1  - Ozaki, Norio
A1  - Perlis, Roy H.
A1  - Pfennig, Andrea
A1  - Potash, James B.
A1  - Reich-Erkelenz, Daniela
A1  - Reif, Andreas
A1  - Reininghaus, Eva
A1  - Richardson, Sara
A1  - Rouleau, Guy A.
A1  - Rybakowski, Janusz K.
A1  - Schalling, Martin
A1  - Schofield, Peter R.
A1  - Schubert, Oliver K.
A1  - Schweizer, Barbara
A1  - Seemüller, Florian
A1  - Grigoroiu-Serbanescu, Maria
A1  - Severino, Giovanni
A1  - Seymour, Lisa R.
A1  - Slaney, Claire
A1  - Smoller, Jordan W.
A1  - Squassina, Alessio
A1  - Stamm, Thomas
A1  - Steele, Jo
A1  - Stopkova, Pavla
A1  - Tighe, Sarah K.
A1  - Tortorella, Alfonso
A1  - Turecki, Gustavo
A1  - Wray, Naomi R.
A1  - Wright, Adam
A1  - Zandi, Peter P.
A1  - Zilles, David
A1  - Bauer, Michael
A1  - Rietschel, Marcella
A1  - McMahon, Francis J.
A1  - Schulze, Thomas G.
A1  - Alda, Martin
T1  - Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report
JF  - PLoS ONE
N2  - Objective: The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study. 
Materials and Methods: Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (\(\kappa\))] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling. 
Results: Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (\(\kappa\) = 0.66 and \(\kappa\) = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (\(ICC_1 = 0.71\) and \(ICC_2 = 0.75\), respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders). 
Conclusions: We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.
KW  - age
KW  - observer agreement
KW  - prophylactic lithium
KW  - mapping susceptibility genes
KW  - mood disorders
KW  - onset
KW  - association
KW  - reliability
KW  - morality
KW  - illness
Y1  - 2013
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-130938
VL  - 8
IS  - 6
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  - 
TY  - JOUR
A1  - Biere, Silvia
A1  - Kranz, Thorsten M.
A1  - Matura, Silke
A1  - Petrova, Kristiyana
A1  - Streit, Fabian
A1  - Chiocchetti, Andreas G.
A1  - Grimm, Oliver
A1  - Brum, Murielle
A1  - Brunkhorst-Kanaan, Natalie
A1  - Oertel, Viola
A1  - Malyshau, Aliaksandr
A1  - Pfennig, Andrea
A1  - Bauer, Michael
A1  - Schulze, Thomas G.
A1  - Kittel-Schneider, Sarah
A1  - Reif, Andreas
T1  - Risk Stratification for Bipolar Disorder Using Polygenic Risk Scores Among Young High-Risk Adults
JF  - Frontiers in Psychiatry
N2  - Objective: 
Identifying high-risk groups with an increased genetic liability for bipolar disorder (BD) will provide insights into the etiology of BD and contribute to early detection of BD. We used the BD polygenic risk score (PRS) derived from BD genome-wide association studies (GWAS) to explore how such genetic risk manifests in young, high-risk adults. We postulated that BD-PRS would be associated with risk factors for BD.

Methods: 
A final sample of 185 young, high-risk German adults (aged 18–35 years) were grouped into three risk groups and compared to a healthy control group (n = 1,100). The risk groups comprised 117 cases with attention deficit hyperactivity disorder (ADHD), 45 with major depressive disorder (MDD), and 23 help-seeking adults with early recognition symptoms [ER: positive family history for BD, (sub)threshold affective symptomatology and/or mood swings, sleeping disorder]. BD-PRS was computed for each participant. Logistic regression models (controlling for sex, age, and the first five ancestry principal components) were used to assess associations of BD-PRS and the high-risk phenotypes.

Results: 
We observed an association between BD-PRS and combined risk group status (OR = 1.48, p < 0.001), ADHD diagnosis (OR = 1.32, p = 0.009), MDD diagnosis (OR = 1.96, p < 0.001), and ER group status (OR = 1.7, p = 0.025; not significant after correction for multiple testing) compared to healthy controls.

Conclusions: 
In the present study, increased genetic risk for BD was a significant predictor for MDD and ADHD status, but not for ER. These findings support an underlying shared risk for both MDD and BD as well as ADHD and BD. Improving our understanding of the underlying genetic architecture of these phenotypes may aid in early identification and risk stratification.
KW  - polygenic risk score
KW  - bipolar disorder
KW  - genetic phenotypes
KW  - depression
KW  - ADHD
KW  - early recognition
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-214976
VL  - 11
ER  -