Browsing by Author "Gershon, Elliot"

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    Characterisation of age and polarity at onset in bipolar disorder
    (Cambridge University Press, 2021-12) Kalman, Janos L.; Olde Loohuis, Loes M.; Vreeker, Annabel; McQuillin, Andrew; Stahl, Eli A.; Ruderfer, Douglas; Grigoroiu-Serbanescu, Maria; Panagiotaropoulou, Georgia; Ripke, Stephan; Bigdeli, Tim B.; Stein, Frederike; Meller, Tina; Meinert, Susanne; Pelin, Helena; Streit, Fabian; Papiol, Sergi; Adams, Mark J.; Adolfsson, Rolf; Adorjan, Kristina; Agartz, Ingrid; Aminoff, Sofie R.; Anderson-Schmidt, Heike; Andreassen, Ole A.; Ardau, Raffaella; Aubry, Jean-Michel; Balaban, Ceylan; Bass, Nicholas; Baune, Bernhard T.; Bellivier, Frank; Benabarre, Antoni; Bengesser, Susanne; Berrettini, Wade H.; Boks, Marco P.; Bromet, Evelyn J.; Brosch, Katharina; Budde, Monika; Byerley, William; Cervantes, Pablo; Chillotti, Catina; Cichon, Sven; Clark, Scott R.; Comes, Ashley L.; Corvin, Aiden; Coryell, William; Craddock, Nick; Craig, David W.; Croarkin, Paul E.; Cruceanu, Cristiana; Czerski, Piotr M.; Dalkner, Nina; Dannlowski, Udo; Degenhardt, Franziska; Del Zompo, Maria; DePaulo, J. Raymond; Djurovic, Srdjan; Edenberg, Howard J.; Al Eissa, Mariam; Elvsåshagen, Torbjørn; Etain, Bruno; Fanous, Ayman H.; Fellendorf, Frederike; Fiorentino, Alessia; Forstner, Andreas J.; Frye, Mark A.; Fullerton, Janice M.; Gade, Katrin; Garnham, Julie; Gershon, Elliot; Gill, Michael; Goes, Fernando S.; Gordon-Smith, Katherine; Grof, Paul; Guzman-Parra, Jose; Hahn, Tim; Hasler, Roland; Heilbronner, Maria; Heilbronner, Urs; Jamain, Stephane; Jimenez, Esther; Jones, Ian; Jones, Lisa; Jonsson, Lina; Kahn, Rene S.; Kelsoe, John R.; Kennedy, James L.; Kircher, Tilo; Kirov, George; Kittel-Schneider, Sarah; Klöhn-Saghatolislam, Farah; Knowles, James A.; Kranz, Thorsten M.; Lagerberg, Trine Vik; Landen, Mikael; Lawson, William B.; Leboyer, Marion; Li, Qingqin S.; Maj, Mario; Malaspina, Dolores; Manchia, Mirko; Mayoral, Fermin; McElroy, Susan L.; McInnis, Melvin G.; McIntosh, Andrew M.; Medeiros, Helena; Melle, Ingrid; Milanova, Vihra; Mitchell, Philip B.; Monteleone, Palmiero; Monteleone, Alessio Maria; Nöthen, Markus M.; Novak, Tomas; Nurnberger, John I.; O'Brien, Niamh; O'Connell, Kevin S.; O'Donovan, Claire; O'Donovan, Michael C.; Opel, Nils; Ortiz, Abigail; Owen, Michael J.; Pålsson, Erik; Pato, Carlos; Pato, Michele T.; Pawlak, Joanna; Pfarr, Julia-Katharina; Pisanu, Claudia; Potash, James B.; Rapaport, Mark H.; Reich-Erkelenz, Daniela; Reif, Andreas; Reininghaus, Eva; Repple, Jonathan; Richard-Lepouriel, Hélène; Rietschel, Marcella; Ringwald, Kai; Roberts, Gloria; Rouleau, Guy; Schaupp, Sabrina; Scheftner, William A.; Schmitt, Simon; Schofield, Peter R.; Schubert, K. Oliver; Schulte, Eva C.; Schweizer, Barbara; Senner, Fanny; Severino, Giovanni; Sharp, Sally; Slaney, Claire; Smeland, Olav B.; Sobell, Janet L.; Squassina, Alessio; Stopkova, Pavla; Strauss, John; Tortorella, Alfonso; Turecki, Gustavo; Twarowska-Hauser, Joanna; Veldic, Marin; Vieta, Eduard; Vincent, John B.; Xu, Wei; Zai, Clement C.; Zandi, Peter P.; Psychiatric Genomics Consortium (PGC) Bipolar Disorder Working Group; International Consortium on Lithium Genetics (ConLiGen); Colombia-US Cross Disorder Collaboration in Psychiatric Genetics; Di Florio, Arianna; Smoller, Jordan W.; Biernacka, Joanna M.; McMahon, Francis J.; Alda, Martin; Müller-Myhsok, Bertram; Koutsouleris, Nikolaos; Falkai, Peter; Freimer, Nelson B.; Andlauer, Till F.M.; Schulze, Thomas G.; Ophoff, Roel A.; Biochemistry and Molecular Biology, School of Medicine
    Background: Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims: To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method: Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results: Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = -0.34 years, s.e. = 0.08), major depression (β = -0.34 years, s.e. = 0.08), schizophrenia (β = -0.39 years, s.e. = 0.08), and educational attainment (β = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions: AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
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    Clinical predictors of non-response to lithium treatment in the Pharmacogenomics of Bipolar Disorder (PGBD) study
    (Wiley, 2021) Lin, Yian; Maihofer, Adam X.; Stapp, Emma; Ritchey, Megan; Alliey‐Rodriguez, Ney; Anand, Amit; Balaraman, Yokesh; Berrettini, Wade H.; Bertram, Holli; Bhattacharjee, Abesh; Calkin, Cynthia V.; Conroy, Carla; Coryell, William; D'Arcangelo, Nicole; DeModena, Anna; Biernacka, Joanna M.; Fisher, Carrie; Frazier, Nicole; Frye, Mark; Gao, Keming; Garnham, Julie; Gershon, Elliot; Glazer, Kara; Goes, Fernando S.; Goto, Toyomi; Karberg, Elizabeth; Harrington, Gloria; Jakobsen, Petter; Kamali, Masoud; Kelly, Marisa; Leckband, Susan G.; Lohoff, Falk W.; Stautland, Andrea; McCarthy, Michael J.; McInnis, Melvin G.; Mondimore, Francis; Morken, Gunnar; Nurnberger, John I.; Oedegaard, Ketil J.; Syrstad, Vigdis Elin Giever; Ryan, Kelly; Schinagle, Martha; Schoeyen, Helle; Andreassen, Ole A.; Shaw, Marth; Shilling, Paul D.; Slaney, Claire; Tarwater, Bruce; Calabrese, Joseph R.; Alda, Martin; Nievergelt, Caroline M.; Zandi, Peter P.; Kelsoe, John R.; Psychiatry, School of Medicine
    Background Lithium is regarded as a first-line treatment for bipolar disorder (BD), but partial response and non-response commonly occurs. There exists a need to identify lithium non-responders prior to initiating treatment. The Pharmacogenomics of Bipolar Disorder (PGBD) Study was designed to identify predictors of lithium response. Methods The PGBD Study was an eleven site prospective trial of lithium treatment in bipolar I disorder. Subjects were stabilized on lithium monotherapy over 4 months and gradually discontinued from all other psychotropic medications. After ensuring a sustained clinical remission (defined by a score of ≤3 on the CGI for 4 weeks) had been achieved, subjects were followed for up to 2 years to monitor clinical response. Cox proportional hazard models were used to examine the relationship between clinical measures and time until failure to remit or relapse. Results A total of 345 individuals were enrolled into the study and included in the analysis. Of these, 101 subjects failed to remit or relapsed, 88 achieved remission and continued to study completion, and 156 were terminated from the study for other reasons. Significant clinical predictors of treatment failure (p < 0.05) included baseline anxiety symptoms, functional impairments, negative life events and lifetime clinical features such as a history of migraine, suicidal ideation/attempts, and mixed episodes, as well as a chronic course of illness. Conclusions In this PGBD Study of lithium response, several clinical features were found to be associated with failure to respond to lithium. Future validation is needed to confirm these clinical predictors of treatment failure and their use clinically to distinguish who will do well on lithium before starting pharmacotherapy.
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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.