TY - JOUR A1 - Weber, Heike A1 - Maihofer, Adam X. A1 - Jaksic, Nenad A1 - Bojic, Elma Feric A1 - Kucukalic, Sabina A1 - Dzananovic, Emina Sabic A1 - Uka, Aferdita Goci A1 - Hoxha, Blerina A1 - Haxhibeqiri, Valdete A1 - Haxhibeqiri, Shpend A1 - Kravic, Nermina A1 - Umihanic, Mirnesa Muminovic A1 - Franc, Ana Cima A1 - Babic, Romana A1 - Pavlovic, Marko A1 - Mehmedbasic, Alma Bravo A1 - Aukst-Margetic, Branka A1 - Kucukalic, Abdulah A1 - Marjanovic, Damir A1 - Babic, Dragan A1 - Jakovljevic, Miro A1 - Sinanovic, Osman A1 - Avidbegović, Esmina A1 - Agani, Ferid A1 - Warrings, Bodo A1 - Domschke, Katharina A1 - Nievergelt, Caroline M. A1 - Dzubur-Kulenovic, Alma A1 - Erhardt, Angelika T1 - Association of polygenic risk scores, traumatic life events and coping strategies with war-related PTSD diagnosis and symptom severity in the South Eastern Europe (SEE)-PTSD cohort JF - Journal of Neural Transmission N2 - Objectives Posttraumatic stress disorder (PTSD) is triggered by extremely stressful environmental events and characterized by high emotional distress, re-experiencing of trauma, avoidance and hypervigilance. The present study uses polygenic risk scores (PRS) derived from the UK Biobank (UKBB) mega-cohort analysis as part of the PGC PTSD GWAS effort to determine the heritable basis of PTSD in the South Eastern Europe (SEE)-PTSD cohort. We further analyzed the relation between PRS and additional disease-related variables, such as number and intensity of life events, coping, sex and age at war on PTSD and CAPS as outcome variables. Methods Association of PRS, number and intensity of life events, coping, sex and age on PTSD were calculated using logistic regression in a total of 321 subjects with current and remitted PTSD and 337 controls previously subjected to traumatic events but not having PTSD. In addition, PRS and other disease-related variables were tested for association with PTSD symptom severity, measured by the Clinician Administrated PTSD Scale (CAPS) by liner regression. To assess the relationship between the main outcomes PTSD diagnosis and symptom severity, each of the examined variables was adjusted for all other PTSD related variables. Results The categorical analysis showed significant polygenic risk in patients with remitted PTSD and the total sample, whereas no effects were found on symptom severity. Intensity of life events as well as the individual coping style were significantly associated with PTSD diagnosis in both current and remitted cases. The dimensional analyses showed as association of war-related frequency of trauma with symptom severity, whereas the intensity of trauma yielded significant results independently of trauma timing in current PTSD. Conclusions The present PRS application in the SEE-PTSD cohort confirms modest but significant polygenic risk for PTSD diagnosis. Environmental factors, mainly the intensity of traumatic life events and negative coping strategies, yielded associations with PTSD both categorically and dimensionally with more significant p-values. This suggests that, at least in the present cohort of war-related trauma, the association of environmental factors and current individual coping strategies with PTSD psychopathology was stronger than the polygenic risk. KW - life events KW - PTSD KW - CAPS KW - polygenic risk score KW - coping style Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-268541 SN - 1435-1463 VL - 129 IS - 5-6 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 -