@article{GrimmWeberKittelSchneideretal.2020, author = {Grimm, Oliver and Weber, Heike and Kittel-Schneider, Sarah and Kranz, Thorsten M. and Jacob, Christian P. and Lesch, Klaus-Peter and Reif, Andreas}, title = {Impulsivity and Venturesomeness in an Adult ADHD Sample: Relation to Personality, Comorbidity, and Polygenic Risk}, series = {Frontiers in Psychiatry}, volume = {11}, journal = {Frontiers in Psychiatry}, issn = {1664-0640}, doi = {10.3389/fpsyt.2020.557160}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-219751}, year = {2020}, abstract = {While impulsivity is a basic feature of attention-deficit/hyperactivity disorder (ADHD), no study explored the effect of different components of the Impulsiveness (Imp) and Venturesomeness (Vent) scale (IV7) on psychiatric comorbidities and an ADHD polygenic risk score (PRS). We used the IV7 self-report scale in an adult ADHD sample of 903 patients, 70\% suffering from additional comorbid disorders, and in a subsample of 435 genotyped patients. Venturesomeness, unlike immediate Impulsivity, is not specific to ADHD. We consequently analyzed the influence of Imp and Vent also in the context of a PRS on psychiatric comorbidities of ADHD. Vent shows a distinctly different distribution of comorbidities, e.g., less anxiety and depression. PRS showed no effect on different ADHD comorbidities, but correlated with childhood hyperactivity. In a complementary analysis using principal component analysis with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition ADHD criteria, revised NEO Personality Inventory, Imp, Vent, and PRS, we identified three ADHD subtypes. These are an impulsive-neurotic type, an adventurous-hyperactive type with a stronger genetic component, and an anxious-inattentive type. Our study thus suggests the importance of adventurousness and the differential consideration of impulsivity in ADHD. The genetic risk is distributed differently between these subtypes, which underlines the importance of clinically motivated subtyping. Impulsivity subtyping might give insights into the organization of comorbid disorders in ADHD and different genetic background.}, language = {en} } @article{BiereKranzMaturaetal.2020, author = {Biere, Silvia and Kranz, Thorsten M. and Matura, Silke and Petrova, Kristiyana and Streit, Fabian and Chiocchetti, Andreas G. and Grimm, Oliver and Brum, Murielle and Brunkhorst-Kanaan, Natalie and Oertel, Viola and Malyshau, Aliaksandr and Pfennig, Andrea and Bauer, Michael and Schulze, Thomas G. and Kittel-Schneider, Sarah and Reif, Andreas}, title = {Risk Stratification for Bipolar Disorder Using Polygenic Risk Scores Among Young High-Risk Adults}, series = {Frontiers in Psychiatry}, volume = {11}, journal = {Frontiers in Psychiatry}, doi = {10.3389/fpsyt.2020.552532}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-214976}, year = {2020}, abstract = {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.}, language = {en} }