@article{Amare2023, abstract = {AbstractLithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium’s possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 1012, R2 = 1.9%) and continuous (P = 6.4 × 109, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22–5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 104, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.}, author = {Amare, Azmeraw T. and Étain, Bruno and Thalamuthu, Anbupalam and Schubert, Klaus Oliver and Hartmann, Simon and Papiol, Sergi and Heilbronner, Urs and Tekola-Ayele, Fasil and Hou, Liping and Hsu, Yi-Hsiang and Shekhtman, Tatyana and Hasler, Roland and Richard-Lepouriel, Hélène and Perroud, Nader and Marie-Claire, Cynthia and Zompo, and Jamain, Stephane and Stegmaier, Sophia and Petrova, Kristiyana and Schuster, Ceylan and Heilbronner, Maria and Kalman, Janos L. and Kohshour, Mojtaba Oraki and Reich-Erkelenz, Daniela and Schaupp, Sabrina K. and Schulte, Eva C. and Senner, Fanny and Vogl, Thomas and Jäger, Markus and Lang, Fabian U. and Juckel, Georg and Reimer, Jens and Spitzer, Carsten and Schmauß, Max and Konrad, Carsten and Schmitt, Andrea and von Hagen, Martin and Wiltfang, Jens and Zimmermann, Jörg and Ritter, Philipp and Matura, Silke and Gryaznova, Anna and Yildiz, Cüneyt and Kircher, Tilo and Schmidt, Julia and Kraft, Vivien and Koch, Marius and Trost, Sarah and Haussleiter, Ida S. and Lambert, Martin and Rohenkohl, Anja C. and Kraft, and Grof, Paul and Hashimoto, Ryota and Hauser, Joanna and Herms, Stefan and Hoffmann, Per and Jiménez, Esther and Kahn, Jean-Pierre and Kassem, Layla and Kuo, Po-Hsiu and Kato, Tadafumi and Kelsoe, John and Kittel-Schneider, Sarah and König, Barbara and Kusumi, Ichiro and Laje, Gonzalo and Landén, Mikael and Lavebratt, Catharina and Leboyer, Marion and Leckband, Susan G. and Tortorella, Alfonso and Manchia, Mirko and Martinsson, Lina and McCarthy, Michael J. and McElroy, Susan L. and Mitjans, Marina and Mondimore, Francis M. and Monteleone, Palmiero and Nievergelt, Caroline M. and Nöthen, Markus M. and Novák, Tomas and O'Donovan, C. and O’Donovan, Claire and Ozaki, Norio and Pfennig, Andrea and Pisanu, Claudia and Potash, James B. and Reif, Andreas and Reininghaus, Eva and Rouleau, Guy A. and Rybakowski, Janusz K. and Schalling, Martin and Schofield, Peter R. and Schweizer, Barbara W. and Severino, Giovanni and Shilling, Paul D. and Millischer, Vincent and Shimoda, Katzutaka and Simhandl, Christian and Slaney, Claire M. and Squassina, Alessio and Stamm, Thomas and Stopkova, Pavla and M., Maj and Maj, Mario and Turecki, Gustavo and Vieta, Eduard and Veeh, Julia and Witt, Stephanie H. and Wright, Adam and Zandi, Peter P. and Mitchell, Philip B. and Rietschel, Marcella and McMahon, Francis J. and Schulze, Thomas G. and Fullerton, Janice M. and Ahmed, Muktar and Degenhardt, Franziska and Adli, Mazda and Akula, Nirmala and Akiyama, Kazufumi and Ardau, Raffaella and Arias, Bárbara and Aubry, Jean-Michel and Backlund, Lena and Bhattacharjee, Abesh Kumar and Bellivier, Frank and Benabarre, Antonio and Bengesser, Susanne and Biernacka, Joanna M. and Birner, Armin and Cervantes, Pablo and Chen, Hsi-Chung and Chillotti, Caterina and Cichon, Sven and Cruceanu, Cristiana and Czerski, Piotr M. and Dalkner, Nina and Etain, B. and DePaulo, J. Raymond and Del Zompo, Maria and Falkai, Peter and Forstner, Andreas J. and Frisen, Louise and Frye, Mark A. and Gard, Sébastien and Garnham, Julie S. and Goes, Fernando S. and Fallgatter, Andreas J. and Ethofer, Thomas and Biere, Silvia and Adorjan, Kristina and Budde, Monika and Anghelescu, Ion-George and Arolt, Volker and Dannlowski, Udo and Dietrich, Detlef E. and Figge, Christian and Andlauer, Till F. M. and Fischer, Andre and Bermpohl, Felix and Falkenberg, Irina and Gade, Kathrin and Grigoroiu-Serbanescu, Maria and Ferensztajn-Rochowiak, Ewa and Colom, Francesc and Bauer, Michael and Alda, Martin and Clark, Scott R. and Baune, Bernhard T.}, doi = {10.1038/s41380-023-02149-1}, journal = {Molecular Psychiatry}, month = {jul}, title = {Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder}, url = {https://oadoi.org/10.1038/s41380-023-02149-1}, year = {2023} } @article{Chan2017, abstract = {AbstractGenome-wide association studies (GWAS) and proteomic studies have provided convincing evidence implicating alterations in immune/inflammatory processes in schizophrenia. However, despite the convergence of evidence, direct links between the genetic and proteomic findings are still lacking for schizophrenia. We investigated associations between single nucleotide polymorphisms (SNPs) from the custom-made PsychArray and the expression levels of 190 multiplex immunoassay profiled serum proteins in 149 schizophrenia patients and 198 matched controls. We identified associations between 81 SNPs and 29 proteins, primarily involved in immune/inflammation responses. Significant SNPxDiagnosis interactions were identified for eight serum proteins including Factor-VII[rs555212], Alpha-1-Antitrypsin[rs11846959], Interferon-Gamma Induced Protein 10[rs4256246] and von-Willebrand-Factor[rs12829220] in the control group; Chromogranin-A[rs9658644], Cystatin-C[rs2424577] and Vitamin K-Dependent Protein S[rs6123] in the schizophrenia group; Interleukin-6 receptor[rs7553796] in both the control and schizophrenia groups. These results suggested that the effect of these SNPs on expression of the respective proteins varies with diagnosis. The combination of patient-specific genetic information with blood biomarker data opens a novel approach to investigate disease mechanisms in schizophrenia and other psychiatric disorders. Our findings not only suggest that blood protein expression is influenced by polymorphisms in the corresponding gene, but also that the effect of certain SNPs on expression of proteins can vary with diagnosis.}, author = {Chan, Man K. and Cooper, Jason D. and Heilmann-Heimbach, Stefanie and Frank, Josef and Witt, Stephanie H. and Nöthen, Markus M. and Steiner, Johann and Rietschel, Marcella and Bahn, Sabine}, doi = {10.1038/s41598-017-12986-0}, journal = {Scientific Reports}, month = {oct}, title = {Associations between SNPs and immune-related circulating proteins in schizophrenia}, url = {https://www.nature.com/articles/s41598-017-12986-0.pdf}, volume = {7}, year = {2017} } @article{Choudhary2023, abstract = {AbstractMaternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.}, author = {Choudhary, Priyanka and Monasso, Giulietta S. and Karhunen, Ville and Ronkainen, Justiina and Mancano, Giulia and Howe, Caitlin G. and Niu, Zhongzheng and Zeng, Xuehuo and Guan, Weihua and Dou, John and Feinberg, Jason I. and Mordaunt, Charles and Pesce, Giancarlo and Baïz, Nour and Alfano, Rossella and Martens, Dries S. and Wang, Congrong and Isaevska, Elena and Keikkala, Elina and Mustaniemi, Sanna and Thio, Chris H. L. and Fraszczyk, Eliza and Tobi, Elmar W. and Starling, Anne P. and Cosin-Tomas, Marta and Urquiza, Jose and Röder, Stefan and Hoang, Thanh T. and Page, Christian and Jima, Dereje D. and House, John S. and Maguire, Rachel L. and Ott, Raffael and Pawlow, Xenia and Sirignano, Lea and Zillich, Lea and Malmberg, Anni and Rauschert, Sebastian and Melton, Phillip and Gong, Tong and Karlsson, Robert and Fore, Ruby and Perng, Wei and Laubach, Zachary M. and Czamara, Darina and Sharp, Gemma and Breton, Carrie V. and Schisterman, Enrique and Yeung, Edwina and Mumford, Sunni L. and Fallin, M. Daniele and LaSalle, Janine M. and Schmidt, Rebecca J. and Bakulski, Kelly M. and Annesi-Maesano, Isabella and Heude, Barbara and Nawrot, Tim S. and Plusquin, Michelle and Ghantous, Akram and Herceg, Zdenko and Nisticò, Lorenza and Vafeiadi, Marina and Kogevinas, Manolis and Vääräsmäki, Marja and Kajantie, Eero and Snieder, Harold and Corpeleijn, Eva and Steegers-Theunissen, Regine P. M. and Yang, Ivana V. and Dabelea, Dana and Fossati, Serena and Zenclussen, Ana C. and Herberth, Gunda and Magnus, Maria and Håberg, Siri E. and London, Stephanie J. and Munthe-Kaas, Monica Cheng and Murphy, Susan K. and Hoyo, Cathrine and Ziegler, Anette-G. and Hummel, Sandra and Witt, Stephanie H. and Streit, Fabian and Frank, Josef and Räikkönen, Katri and Lahti, Jari and Huang, Rae-Chi and Almqvist, Catarina and Hivert, Marie-France and Jaddoe, Vincent W. V. and Järvelin, Marjo-Riitta and Kantomaa, Marko and Felix, Janine F. and Sebert, Sylvain}, doi = {10.1038/s41380-023-02331-5}, journal = {Molecular Psychiatry}, month = {dec}, title = {Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence}, url = {https://oadoi.org/10.1038/s41380-023-02331-5}, year = {2023} } @article{Comes2019, abstract = {AbstractCognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.}, author = {Comes, Ashley L. and Zimmermann, Jörg and Thiel, Andreas and von Hagen, Martin and Wigand, Moritz E. and Witt, Stephanie H. and Wiltfang, Jens and Al, Comes and Schaupp, Sabrina K. and Senner, Fanny and Schulte, Eva C. and Schmauß, Max and Budde, Monika and Reimer, Jens and Adorjan, Kristina and Andlauer, Till F. M. and Reininghaus, Eva and Anderson-Schmidt, Heike and Kalman, Janos L. and Klöhn-Saghatolislam, Farah and Gade, Katrin and Juckel, Georg and Dannlowski, Udo and Reich-Erkelenz, Daniela and Hake, Maria and Tfm, Andlauer and Stierl, Sebastian and Scherk, Harald and Anghelescu, Ion‐George and Heilbronner, Urs and Spitzer, Carsten and Arolt, Volker and Baune, Bernhard T. and Konrad, Carsten and Rietschel, Marcella and Fallgatter, Andreas J. and Nieratschker, Vanessa and Figge, Christian and Schulze, Thomas G. and Koller, Manfred and Becker, Thomas and Jl, Kalman and Jäger, Markus and Dietrich, Detlef E. and Folkerts, Here and Degenhardt, Franziska and Forstner, Andreas J. and Nöthen, Markus M. and Falkai, Peter and Papiol, Sergi}, doi = {10.1038/s41398-019-0547-x}, journal = {Translational Psychiatry}, month = {aug}, title = {The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders}, url = {https://www.nature.com/articles/s41398-019-0547-x.pdf}, volume = {9}, year = {2019} } @article{Forstner2017, abstract = {Bipolar disorder (BD) is a highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. BD shows substantial clinical and genetic overlap with other psychiatric disorders, in particular schizophrenia (SCZ). The genes underlying this etiological overlap remain largely unknown. A recent SCZ genome wide association study (GWAS) by the Psychiatric Genomics Consortium identified 128 independent genome-wide significant single nucleotide polymorphisms (SNPs). The present study investigated whether these SCZ-associated SNPs also contribute to BD development through the performance of association testing in a large BD GWAS dataset (9747 patients, 14278 controls). After re-imputation and correction for sample overlap, 22 of 107 investigated SCZ SNPs showed nominal association with BD. The number of shared SCZ-BD SNPs was significantly higher than expected (p = 1.46x10-8). This provides further evidence that SCZ-associated loci contribute to the development of BD. Two SNPs remained significant after Bonferroni correction. The most strongly associated SNP was located near TRANK1, which is a reported genome-wide significant risk gene for BD. Pathway analyses for all shared SCZ-BD SNPs revealed 25 nominally enriched gene-sets, which showed partial overlap in terms of the underlying genes. The enriched gene-sets included calcium- and glutamate signaling, neuropathic pain signaling in dorsal horn neurons, and calmodulin binding. The present data provide further insights into shared risk loci and disease-associated pathways for BD and SCZ. This may suggest new research directions for the treatment and prevention of these two major psychiatric disorders.}, author = {Forstner, Andreas Josef and Șerbanescu-Grigoroiu, Maria and Hecker, Julian and Hofmann, Andrea and Maaser, Anna and Reinbold, Céline S. and Mühleisen, Thomas W. and Leber, Markus and Strohmaier, Jana and Degenhardt, Franziska and Treutlein, Jens and Mattheisen, Manuel and Schumacher, Johannes and Streit, Fabian and Meier, Sandra and Herms, Stefan and Hoffmann, Per and Lacour, André and Witt, Stephanie H. and Reif, Andreas and Müller-Myhsok, Bertram and Lucae, Susanne and Maier, Wolfgang and Schwarz, Markus and Vedder, Helmut and Kammerer-Ciernioch, Jutta and Pfennig, Andrea and Bauer, Michael and Hautzinger, Martin and Moebus, Susanne and Schenk, Lorena M. and Fischer, Sascha B. and Sivalingam, Sugirthan and Czerski, Piotr M. and Hauser, Joanna and Lissowska, Jolanta and Szeszenia-Dabrowska, Neonila and Brennan, Paul and McKay, James D. and Wright, Adam and Mitchell, Philip B. and Fullerton, Janice M. and Schofield, Peter R. and Montgomery, Grant W. and Medland, Sarah E. and Gordon, Scott D. and Martin, Nicholas G. and Krasnov, Valery and Chuchalin, Alexander and Babadjanova, Gulja and Pantelejeva, Galina and Abramova, Lilia I. and Tiganov, Alexander S. and Polonikov, Alexey and Khusnutdinova, Elza and Alda, Martin and Cruceanu, Cristiana and Rouleau, Guy A. and Turecki, Gustavo and Laprise, Catherine and Rivas, Fabio and Mayoral, Fermin and Kogevinas, Manolis and Grigoroiu-Serbanescu, Maria and Becker, Tim and Schulze, Thomas G. and Rietschel, Marcella and Cichon, Sven and Fier, Heide and Nöthen, Markus Maria}, doi = {10.1371/journal.pone.0171595}, journal = {PLoS ONE}, month = {jan}, pages = {e0171595}, title = {Identification of shared risk loci and pathways for bipolar disorder and schizophrenia}, url = {https://doi.org/10.1371/journal.pone.0171595}, volume = {12}, year = {2017} } @article{Gilles2018, author = {Gilles, Maria and Otto, Henrike and Wolf, Isabell A. C. and Scharnholz, Barbara and Peus, Verena and Schredl, Michael and Sütterlin, Marc W. and Witt, Stephanie H. and Rietschel, Marcella and Laucht, Manfred and Deuschle, Michael}, doi = {10.1016/j.psyneuen.2018.04.022}, journal = {Psychoneuroendocrinology}, month = {aug}, pages = {152-161}, title = {Maternal hypothalamus-pituitary-adrenal (HPA) system activity and stress during pregnancy: Effects on gestational age and infant’s anthropometric measures at birth}, url = {https://oadoi.org/10.1016/j.psyneuen.2018.04.022}, volume = {94}, year = {2018} } @article{Goltermann2020, abstract = {AbstractChildhood maltreatment is associated with cognitive deficits that in turn have been predictive for therapeutic outcome in psychiatric patients. However, previous studies have either investigated maltreatment associations with single cognitive domains or failed to adequately control for confounders such as depression, socioeconomic environment, and genetic predisposition. We aimed to isolate the relationship between childhood maltreatment and dysfunction in diverse cognitive domains, while estimating the contribution of potential confounders to this relationship, and to investigate gene–environment interactions. We included 547 depressive disorder and 670 healthy control participants (mean age: 34.7 years, SD = 13.2). Cognitive functioning was assessed for the domains of working memory, executive functioning, processing speed, attention, memory, and verbal intelligence using neuropsychological tests. Childhood maltreatment and parental education were assessed using self-reports, and psychiatric diagnosis was based on DSM-IV criteria. Polygenic scores for depression and for educational attainment were calculated. Multivariate analysis of cognitive domains yielded significant associations with childhood maltreatment (η²p = 0.083, P < 0.001), depression (η²p = 0.097, P < 0.001), parental education (η²p = 0.085, P < 0.001), and polygenic scores for depression (η²p = 0.021, P = 0.005) and educational attainment (η²p = 0.031, P < 0.001). Each of these associations remained significant when including all of the predictors in one model. Univariate tests revealed that maltreatment was associated with poorer performance in all cognitive domains. Thus, environmental, psychopathological, and genetic risk factors each independently affect cognition. The insights of the current study may aid in estimating the potential impact of different loci of interventions for cognitive dysfunction. Future research should investigate if customized interventions, informed by individual risk profiles and related cognitive preconditions, might enhance response to therapeutic treatments.}, author = {Goltermann, Janik and Redlich, Ronny and Grotegerd, Dominik and Dohm, Katharina and Leehr, Elisabeth J. and Böhnlein, Joscha and Förster, Katharina and Meinert, Susanne and Enneking, Verena and Richter, Maike and Repple, Jonathan and DeVillers, Immanuel and Kloecker, Marine and Jansen, Andreas and Krug, Axel and Nenadic, Igor and Brosch, Katharina and Dipl-Psych, Tina Meller and Meller, Tina and Stein, Frederike and Schmitt, Simon and Rietschel, Marcella and Streit, Fabian and Witt, Stephanie H. and Forstner, Andreas J. and Nöthen, Markus M. and Baune, Bernhard T. and Andlauer, Till F. M. and Kircher, Tilo and Opel, Nils and Dannlowski, Udo}, doi = {10.1038/s41386-020-00794-6}, journal = {Neuropsychopharmacology}, month = {aug}, pages = {891-899}, title = {Childhood maltreatment and cognitive functioning: the role of depression, parental education, and polygenic predisposition}, url = {https://oadoi.org/10.1038/s41386-020-00794-6}, volume = {46}, year = {2020} } @article{Hahn2023, abstract = {AbstractMany therapeutic interventions in psychiatry can be viewed as attempts to influence the brain’s large-scale, dynamic network state transitions. Building on connectome-based graph analysis and control theory, Network Control Theory is emerging as a powerful tool to quantify network controllability—i.e., the influence of one brain region over others regarding dynamic network state transitions. If and how network controllability is related to mental health remains elusive. Here, from Diffusion Tensor Imaging data, we inferred structural connectivity and inferred calculated network controllability parameters to investigate their association with genetic and familial risk in patients diagnosed with major depressive disorder (MDD, n = 692) and healthy controls (n = 820). First, we establish that controllability measures differ between healthy controls and MDD patients while not varying with current symptom severity or remission status. Second, we show that controllability in MDD patients is associated with polygenic scores for MDD and psychiatric cross-disorder risk. Finally, we provide evidence that controllability varies with familial risk of MDD and bipolar disorder as well as with body mass index. In summary, we show that network controllability is related to genetic, individual, and familial risk in MDD patients. We discuss how these insights into individual variation of network controllability may inform mechanistic models of treatment response prediction and personalized intervention-design in mental health.}, author = {Hahn, Tim and Winter, Nils R. and Ernsting, Jan and Gruber, Marius and Mauritz, Marco J. and Fisch, Lukas and Leenings, Ramona and Sarink, Kelvin and Blanke, Julian and Holstein, Vincent and Emden, Daniel and Beisemann, Marie and Opel, Nils and Grotegerd, Dominik and van den Heuvel, Martijn P. and Meinert, Susanne and Heindel, Walter and Witt, Stephanie and Rietschel, Marcella and Nöthen, Markus M. and Forstner, Andreas J. and Kircher, Tilo and Nenadic, Igor and Jansen, Andreas and Müller-Myhsok, Bertram and Andlauer, Till F. M. and Walter, Martin and Heuvel, Van Den and Jamalabadi, Hamidreza and Dannlowski, Udo and Repple, Jonathan}, doi = {10.1038/s41380-022-01936-6}, journal = {Molecular Psychiatry}, month = {jan}, pages = {1057-1063}, title = {Genetic, individual, and familial risk correlates of brain network controllability in major depressive disorder}, url = {https://oadoi.org/10.1038/s41380-022-01936-6}, volume = {28}, year = {2023} } @article{Johnson2016, abstract = {It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (beta = 16.1, CI(beta) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (beta = 4.86, CI(beta) = [0.90,8.83], Z = 2.40, p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest.}, author = {Johnson, Emma C. and Howrigan, Daniel P. and Herms, Stefan and Hoffman, Per and Neale, B. M. and Maier, Wolfgang and Mattheisen, Manuel and O’Dushlaine, C. and Müller-Mhysok, Betram and Ripke, S. and Nenadic, Igor and Walters, J. T. R. and Holmans, P. A. and Lee, P. and Rietschel, Marcella and Huang, H. and Ruderfer, Douglas M. and Pers, T. H. and Morris, D. W. and Neale, Benjamin M. and Rujescu, Dan and Schulze, Thomas G. and Simonson, Matthew A. and Strohmaier, Jana and Witt, Stephanie H. and Mowry, B. J. and Stahl, E. A. and Nöthen, M. M. and Robert Cloninger, C. and Morris, Derek and de Haan, L. and Henskens, F. A. and Hirschhorn, J. N. and Hoffmann, P. and Hofman, A. and Hollegaard, M. and Hougaard, D. M. and Ikeda, M. and Joa, I. and Julià, A. and Kahn, R. S. and Kalaydjieva, L. and Karachanak-Yankova, S. and Karjalainen, J. and Kavanagh, D. and Kennedy, J. L. and Khrunin, A. and Kim, Y. and Klovins, J. and Knowles, J. A. and Konte, B. and Kucinskas, and Kucinskiene, Z. A. and Kuzelova-Ptackova, H. and Kähler, A. K. and Laurent, C. and Hong Lee, S. and Legge, S. E. and Lerer, B. and Li, M. and Li, T. and Liang, K.-Y. and Lieberman, J. and Limborska, S. and Loughland, C. M. and Lubinski, J. and Lönnqvist, J. and Macek, M. and Magnusson, P. K. E. and Maher, B. S. and Mallet, J. and Marsal, S. and Mattingsdal, M. and McCarley, R. W. and McDonald, C. and McIntosh, A. M. and Meier, S. and Meijer, C. J. and Melegh, B. and Melle, I. and Mesholam-Gately, R. I. and Metspalu, A. and Michie, P. T. and Milani, L. and Milanova, and Mokrab, Y. and Mors, O. and Murphy, K. C. and Murray, R. M. and Myin-Germeys, I. and Müller-Myhsok, B. and Nelis, M. and Nertney, D. A. and Nestadt, G. and Nicodemus, K. K. and Nikitina-Zake, L. and Nisenbaum, L. and Nordin, A. and O'Callaghan, E. and Oh, S.-Y. and O'Dushlaine, Colm and Olincy, A. and Olsen, L. and Van Os, J. and Pantelis, C. and Papadimitriou, G. N. and Papiol, S. and Parkhomenko, E. and Pato, M. T. and Paunio, T. and Pejovic-Milovancevic, M. and Perkins, D. O. and Pietiläinen, O. and Pimm, J. and Pocklington, A. J. and Powell, J. and Price, A. and Pulver, A. E. and Purcell, S. M. and Quested, D. and Rasmussen, H. B. and Reichenberg, A. and Reimers, and Richards, A. L. and Roffman, J. L. and Roussos, P. and Salomaa, and Sanders, A. R. and Schall, U. and Wolen, A. R. and Schubert, C. R. and Noethen, M. and Wong, E. H. M. and Schwab, S. G. and Scolnick, E. M. and Stahl, Eli A. and Wormley, B. K. and Scott, R. J. and Seidman, L. J. and Xi, H. S. and Shi, J. and Sigurdsson, E. and Zai, C. C. and Silagadze, T. and Zheng, X. and Silverman, J. M. and Sim, K. and Zimprich, F. and Slominsky, P. and Smoller, J. W. and Wray, N. R. and So, H.-C. and Spencer, C. C. A. and Stefansson, H. and Steinberg, S. and Stogmann, E. and Straub, R. E. and Strengman, E. and Scott Stroup, T. and Subramaniam, M. and Suvisaari, J. and Svrakic, D. M. and Szatkiewicz, J. P. and Söderman, E. and Thirumalai, S. and Toncheva, D. and Tosato, S. and Veijola, J. and Waddington, J. and Walsh, D. and Wang, D. and Wang, Q. and Webb, B. T. and Weiser, M. and Wildenauer, D. B. and Williams, N. M. and Williams, S. and Stefansson, K. and Visscher, P. M. and Mowry, Bryan J. and Nöthen, Markus M. and Hultman, C. M. and Iwata, N. and Jablensky, A. and Jönsson, E. G. and Kendler, K. S. and Kirov, G. and Knight, J. and Lencz, T. and Levinson, D. F. and Li, Q. S. and Liu, J. and Malhotra, A. K. and McCarroll, S. A. and McQuillin, A. and Moran, J. L. and Mortensen, P. B. and Ophoff, R. A. and Owen, M. J. and Palotie, A. and Pato, C. N. and Petryshen, T. L. and Posthuma, D. and Riley, B. P. and Sham, P. C. and Sklar, P. and Weinberger, D. R. and Wendland, and Werge, T. and O'Donovan, M. C. and Sullivan, Patrick F. and Sullivan, P. F. and Keller, Matthew C. and Bjelland, Douglas W. and Abdellaoui, Abdel and Breen, Gerome and Borglum, Anders and Cichon, Sven and Degenhardt, Franziska and Forstner, Andreas J. and Frank, Josef and Genovese, Giulio and Corvin, A. and Farh, K.-H. and Bulik-Sullivan, B. and Collier, D. A. and Agartz, I. and Agerbo, E. and Albus, M. and Alexander, M. and Amin, F. and Bacanu, S. A. and Begemann, M. and Belliveau, R. A. and Bene, J. and Bergen, S. E. and Bevilacqua, E. and Bigdeli, T. B. and Black, D. W. and Bruggeman, R. and Buccola, N. G. and Buckner, R. L. and Byerley, W. and Cahn, W. and Cai, G. and Campion, D. and Cantor, R. M. and Carr, V. J. and Carrera, N. and Catts, S. and Chambert, K. D. and Chan, R. C. K. and Chen, R. Y. L. and Chen, E. Y. H. and Cheng, W. and Cheung, E. F. C. and Chong, S. A. and Cohen, D. and Cohen, N. and Cormican, P. and Craddock, N. and Crowley, J. J. and Curtis, D. and Davidson, M. and Davis, K. L. and Del Favero, J. and Demontis, D. and Dikeos, D. and Dinan, T. and Djurovic, S. and Donohoe, G. and Drapeau, E. and Duan, J. and Dudbridge, F. and Durmishi, N. and Eichhammer, P. and Eriksson, J. and Escott-Price, and Essioux, L. and Fanous, A. H. and Farrell, and Franke, L. and Freedman, R. and Freimer, N. B. and Friedl, M. and Friedman, J. I. and Fromer, M. and Georgieva, L. and Giegling, I. and Giusti-Rodríguez, P. and Godard, S. and Goldstein, J. I. and Golimbet, and Gopal, S. and Gratten, J. and Hammer, C. and Hamshere, M. L. and Hansen, M. and Hansen, T. and Haroutunian, and Hartmann, A. M. and Chee Keong, J. L. and Anthony O'Neill, F. and Adolfsson, R. and Andreassen, O. A. and Blackwood, D. H. R. and Bramon, E. and Buxbaum, and Børglum, A. D. and Darvasi, A. and Heilmann-Heimbach, Stefanie and Domenici, E. and Ehrenreich, H. and Esko, T. and Gejman, P. and Gill, M. and Gurling, H. and Clair, D. S. and Daly, M. J. and Consortium, Schizophrenia Working Group of the Psychiatric Genomics}, doi = {10.1371/journal.pgen.1006343}, journal = {PLoS Genetics}, month = {oct}, pages = {e1006343}, title = {No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study}, url = {https://doi.org/10.1371/journal.pgen.1006343}, volume = {12}, year = {2016} } @article{Kohshour2022, abstract = {AbstractThe diagnostic criteria for schizophrenia (SCZ) and bipolar disorder (BD) are based on clinical assessments of symptoms. In this pilot study, we applied high-throughput antibody-based protein profiling to serum samples of healthy controls and individuals with SCZ and BD with the aim of identifying differentially expressed proteins in these disorders. Moreover, we explored the influence of polygenic burden for SCZ and BD on the serum levels of these proteins. Serum samples from 113 individuals with SCZ and 125 with BD from the PsyCourse Study and from 44 healthy controls were analyzed by using a set of 155 antibodies in an antibody-based assay targeting a selected panel of 95 proteins. For the cases, genotyping and imputation were conducted for DNA samples and SCZ and BD polygenic risk scores (PRS) were calculated. Univariate linear and logistic models were used for association analyses. The comparison between SCZ and BD revealed two serum proteins that were significantly elevated in BD after multiple testing adjustment: “complement C9” and “Interleukin 1 Receptor Accessory Protein”. Moreover, the first principal component of variance in the proteomics dataset differed significantly between SCZ and BD. After multiple testing correction, SCZ-PRS, BD-PRS, and SCZ-vs-BD–PRS were not significantly associated with the levels of the individual proteins or the values of the proteome principal components indicating no detectable genetic effects. Overall, our findings contribute to the evidence suggesting that the analysis of circulating proteins could lead to the identification of distinctive biomarkers for SCZ and BD. Our investigation warrants replication in large-scale studies to confirm these findings.}, author = {Kohshour, Mojtaba Oraki and Oraki Kohshour, Mojtaba and Kannaiyan, Nirmal R. and Falk, August Jernbom and Papiol, Sergi and Heilbronner, Urs and Budde, Monika and Kalman, Janos L. and Schulte, Eva C. and Rietschel, Marcella and Witt, Stephanie and Forstner, Andreas J. and Heilmann-Heimbach, Stefanie and Nöthen, Markus M. and Spitzer, Carsten and Malchow, Berend and Müller, Thorsten and Wiltfang, Jens and Falkai, Peter and Schmitt, Andrea and Rossner, Moritz J. and Nilsson, Peter and Schulze, Thomas G.}, doi = {10.1038/s41398-022-02228-x}, journal = {Translational Psychiatry}, month = {nov}, title = {Comparative serum proteomic analysis of a selected protein panel in individuals with schizophrenia and bipolar disorder and the impact of genetic risk burden on serum proteomic profiles}, url = {https://doi.org/10.1038/s41398-022-02228-x}, volume = {12}, year = {2022} } @article{Kotsakis Ruehlmann2023, author = {Kotsakis Ruehlmann, Anna and Sammallahti, Sara and Cortés Hidalgo, Andrea P. and Bakulski, Kelly M. and Binder, Elisabeth B. and Campbell, Megan Loraine and Caramaschi, Doretta and Cecil, Charlotte A. M. and Colicino, Elena and Cruceanu, Cristiana and Czamara, Darina and Dieckmann, Linda and Dou, John and Felix, Janine F. and Frank, Josef and Håberg, Siri E. and Herberth, Gunda and Hoang, Thanh T. and Houtepen, Lotte C. and Hüls, Anke and Koen, Nastassja and London, Stephanie J. and Magnus, Maria C. and Mancano, Giulia and Mulder, Rosa H. and Page, Christian M. and Räikkönen, Katri and Röder, Stefan and Schmidt, Rebecca J. and Send, Tabea S. and Sharp, Gemma and Stein, Dan J. and Streit, Fabian and Tuhkanen, Johanna and Witt, Stephanie H. and Zar, Heather J. and Zenclussen, Ana C. and Zhang, Yining and Zillich, Lea and Wright, Rosalind and Lahti, Jari and Brunst, Kelly J.}, doi = {10.1038/s41380-023-02010-5}, journal = {Molecular Psychiatry}, month = {mar}, title = {Epigenome-wide meta-analysis of prenatal maternal stressful life events and newborn DNA methylation}, url = {https://oadoi.org/10.1038/s41380-023-02010-5}, year = {2023} } @article{Opel2018, author = {Opel, Nils and Amare, Azmeraw T. and Redlich, Ronny and Repple, Jonathan and Kaehler, Claas and Grotegerd, Dominik and Dohm, Katharina and Zaremba, Dario and Leehr, Elisabeth J. and Böhnlein, Joscha and Förster, Katharina and Bürger, Christian and Meinert, Susanne and Enneking, Verena and Emden, Daniel and Leenings, Ramona and Winter, Nils and Hahn, Tim and Heindel, Walter and Bauer, Jochen and Wilhelms, David and Schmitt, Simon and Jansen, Andreas and Krug, Axel and Nenadic, Igor and Rietschel, Marcella and Witt, Stephanie and Forstner, Andreas J. and Nöthen, Markus M. and Kircher, Tilo and Arolt, Volker and Baune, Bernhard T. and Dannlowski, Udo}, doi = {10.1038/s41380-018-0236-9}, journal = {Molecular Psychiatry}, month = {sep}, pages = {3422-3431}, title = {Cortical surface area alterations shaped by genetic load for neuroticism}, url = {https://oadoi.org/10.1038/s41380-018-0236-9}, volume = {25}, year = {2018} } @article{Pelin2021, abstract = {AbstractPsychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1–3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.}, author = {Pelin, Helena and Ising, Marcus and Stein, Frederike and Meinert, Susanne and Winter, Nils R. and Meller, Tina and Brosch, Katharina and Krug, Axel and Leenings, Ramona and Lemke, Hannah and Forstner, Andreas J. and Nenadić, Igor and Nöthen, Markus M. and Nr, Winter and Thiel, Katharina and Heilmann-Heimbach, Stefanie and Waltemate, Lena and Opel, Nils and Winter, Alexandra and Repple, Jonathan and Pfarr, Julia and Ringwald, Kai and Witt, Stephanie and Schmitt, Simon and Streit, Fabian and Rietschel, Marcella and Dannlowski, Udo and Kircher, Tilo and Aj, Forstner and Hahn, Tim and Müller-Myhsok, Bertram and Andlauer, Till F. M. and Tfm, Andlauer}, doi = {10.1038/s41386-021-01051-0}, journal = {Neuropsychopharmacology}, month = {jun}, pages = {1895-1905}, title = {Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning}, url = {https://www.nature.com/articles/s41386-021-01051-0.pdf}, volume = {46}, year = {2021} } @article{Ringwald2021, author = {Ringwald, Kai G. and Meller, Tina and Schmitt, Simon and Andlauer, Till F. M. and Stein, Frederike and Brosch, Katharina and Pfarr, Julia-Katharina and Steinsträter, Olaf and Meinert, Susanne and Lemke, Hannah and Waltemate, Lena and Thiel, Katharina and Grotegerd, Dominik and Enneking, Verena and Klug, Melissa and Jansen, Andreas and Forstner, Andreas J. and Streit, Fabian and Witt, Stephanie H. and Rietschel, Marcella and Müller-Myhsok, Bertram and Nöthen, Markus M. and Dannlowski, Udo and Krug, Axel and Nenadić, Igor and Kircher, Tilo}, doi = {10.1016/j.nicl.2021.102683}, journal = {NeuroImage: Clinical}, month = {jan}, pages = {102683}, title = {Interaction of developmental factors and ordinary stressful life events on brain structure in adults}, url = {https://doi.org/10.1016/j.nicl.2021.102683}, volume = {30}, year = {2021} } @article{Thalamuthu2021, author = {Thalamuthu, Anbupalam and Mills, Natalie T. and Berger, Klaus and Minnerup, Heike and Grotegerd, Dominik and Dannlowski, Udo and Meinert, Susanne and Opel, Nils and Repple, Jonathan and Gruber, Marius and Nenadić, Igor and Stein, Frederike and Brosch, Katharina and Meller, Tina and Pfarr, Julia-Katharina and Forstner, Andreas J. and Hoffmann, Per and Nöthen, Markus M. and Witt, Stephanie and Rietschel, Marcella and Kircher, Tilo and Adams, Mark and McIntosh, Andrew M. and Porteous, David J. and Deary, Ian J. and Hayward, Caroline and Campbell, Archie and Grabe, Hans Jörgen and Teumer, Alexander and Homuth, Georg and van der Auwera-Palitschka, Sandra and Schubert, K. Oliver and Baune, Bernhard T.}, doi = {10.1038/s41380-021-01379-5}, journal = {Molecular Psychiatry}, month = {nov}, pages = {1111-1119}, title = {Genome-wide interaction study with major depression identifies novel variants associated with cognitive function}, url = {https://oadoi.org/10.1038/s41380-021-01379-5}, volume = {27}, year = {2021} } @article{Thiel2024, abstract = {AbstractPatients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations. N = 73 BD-I, n = 63 BD-II patients and n = 136 matched HC were included. Using voxel-based morphometry and tract-based spatial statistics, main effects of group in GMV and fractional anisotropy (FA) were analyzed. Associations between clinical and genetic features and GMV or FA were calculated using regression models. For FA but not GMV, we found significant differences between groups. BD-I patients showed lower FA compared with BD-II patients (ptfce-FWE = 0.006), primarily in the anterior corpus callosum. Compared with HC, BD-I patients exhibited lower FA in widespread clusters (ptfce-FWE < 0.001), including almost all major projection, association, and commissural fiber tracts. BD-II patients also demonstrated lower FA compared with HC, although less pronounced (ptfce-FWE = 0.049). The results remained unchanged after controlling for clinical and genetic features, for which no independent associations with FA or GMV emerged. Our findings suggest that, at a neurobiological level, BD subtypes may reflect distinct degrees of disease expression, with increasing WM microstructure disruption from BD-II to BD-I. This differential magnitude of microstructural alterations was not clearly linked to clinical and genetic variables. These findings should be considered when discussing the classification of BD subtypes within the spectrum of affective disorders.}, author = {Thiel, Katharina and Lemke, Hannah and Winter, Alexandra and Flinkenflügel, Kira and Waltemate, Lena and Bonnekoh, Linda and Grotegerd, Dominik and Dohm, Katharina and Hahn, Tim and Förster, Katharina and Kanske, Philipp and Repple, Jonathan and Opel, Nils and Redlich, Ronny and David, Friederike and Forstner, Andreas J. and Stein, Frederike and Brosch, Katharina and Thomas-Odenthal, Florian and Usemann, Paula and Teutenberg, Lea and Straube, Benjamin and Alexander, Nina and Jamalabadi, Hamidreza and Jansen, Andreas and Witt, Stephanie H. and Andlauer, Till F. M. and Pfennig, Andrea and Bauer, Michael and Nenadić, Igor and Kircher, Tilo and Meinert, Susanne and Dannlowski, Udo}, doi = {10.1038/s41386-024-01812-7}, journal = {Neuropsychopharmacology}, month = {feb}, title = {White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls – exploring associations with disease course and polygenic risk}, url = {https://oadoi.org/10.1038/s41386-024-01812-7}, year = {2024} } @article{von Hagen2021, abstract = {AbstractAs early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke’s pseudo-R2: 1.3–7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.}, author = {von Hagen, Martin and Zimmermann, Jörg and Smigielski, Lukasz and Papiol, Sergi and Theodoridou, Anastasia and Heekeren, Karsten and Comes, Ashley L. and Gade, Katrin and Gerstenberg, Miriam and Heilbronner, Maria and Heilbronner, Urs and Wotruba, Diana and Kalman, Janos L. and Klöhn-Saghatolislam, Farahnaz and Reich-Erkelenz, Daniela and Buechler, Roman and Schaupp, Sabrina K. and Schulte, Eva C. and Senner, Fanny and Hoffmann, Per and Anghelescu, Ion-George and Arolt, Volker and Baune, Bernhard T. and Herms, Stefan and Dannlowski, Udo and Dietrich, Detlef E. and Fallgatter, Andreas J. and Adorjan, Kristina and Figge, Christian and Jäger, Markus and Anderson-Schmidt, Heike and Juckel, Georg and Konrad, Carsten and Nieratschker, Vanessa and Budde, Monika and Reimer, Jens and Reininghaus, Eva and Schmauß, Max and Spitzer, Carsten and Wiltfang, Jens and Gryaznova, Anna and Flatau-Nagel, Laura and Reitt, Markus and Meyers, Milena and Emons, Barbara and Haußleiter, Ida Sybille and Lang, Fabian U. and Becker, Thomas and Wigand, Moritz E. and Witt, Stephanie H. and Degenhardt, Franziska and Forstner, Andreas J. and Rietschel, Marcella and Nöthen, Markus M. and Andlauer, Till F. M. and Rössler, Wulf and Walitza, Susanne and Falkai, Peter and Schulze, Thomas G. and Grünblatt, Edna}, doi = {10.1038/s41398-021-01720-0}, journal = {Translational Psychiatry}, month = {nov}, title = {Polygenic risk scores across the extended psychosis spectrum}, url = {https://doi.org/10.1038/s41398-021-01720-0}, volume = {11}, year = {2021} } @article{Yüksel2017, author = {Yüksel, Dilara and Dietsche, Bruno and Forstner, Andreas J. and Witt, Stephanie H. and Maier, Robert and Rietschel, Marcella and Konrad, Carsten and Nöthen, Markus M. and Dannlowski, Udo and Baune, Bernhard T. and Kircher, Tilo and Krug, Axel}, doi = {10.1016/j.pnpbp.2017.06.010}, journal = {Progress in Neuro-Psychopharmacology and Biological Psychiatry}, month = {oct}, pages = {67-76}, title = {Polygenic risk for depression and the neural correlates of working memory in healthy subjects}, url = {https://oadoi.org/10.1016/j.pnpbp.2017.06.010}, volume = {79}, year = {2017} } @article{Zillich2021, abstract = {AbstractAlcohol use disorder (AUD) is closely linked to the brain regions forming the neurocircuitry of addiction. Postmortem human brain tissue enables the direct study of the molecular pathomechanisms of AUD. This study aims to identify these mechanisms by examining differential DNA-methylation between cases with severe AUD (n = 53) and controls (n = 58) using a brain-region-specific approach, in which sample sizes ranged between 46 and 94. Samples of the anterior cingulate cortex (ACC), Brodmann Area 9 (BA9), caudate nucleus (CN), ventral striatum (VS), and putamen (PUT) were investigated. DNA-methylation levels were determined using the Illumina HumanMethylationEPIC Beadchip. Epigenome-wide association analyses were carried out to identify differentially methylated CpG-sites and regions between cases and controls in each brain region. Weighted correlation network analysis (WGCNA), gene-set, and GWAS-enrichment analyses were performed. Two differentially methylated CpG-sites were associated with AUD in the CN, and 18 in VS (q < 0.05). No epigenome-wide significant CpG-sites were found in BA9, ACC, or PUT. Differentially methylated regions associated with AUD case-/control status (q < 0.05) were found in the CN (n = 6), VS (n = 18), and ACC (n = 1). In the VS, the WGCNA-module showing the strongest association with AUD was enriched for immune-related pathways. This study is the first to analyze methylation differences between AUD cases and controls in multiple brain regions and consists of the largest sample to date. Several novel CpG-sites and regions implicated in AUD were identified, providing a first basis to explore epigenetic correlates of AUD.}, author = {Zillich, Lea and Frank, Josef and Streit, Fabian and Friske, Marion M. and Foo, Jerome C. and Sirignano, Lea and Heilmann-Heimbach, Stefanie and Dukal, Helene and Degenhardt, Franziska and Hoffmann, Per and Hansson, Anita C. and Nöthen, Markus M. and Rietschel, Marcella and Spanagel, Rainer and Witt, Stephanie H.}, doi = {10.1038/s41386-021-01228-7}, journal = {Neuropsychopharmacology}, month = {nov}, pages = {832-839}, title = {Epigenome-wide association study of alcohol use disorder in five brain regions}, url = {https://oadoi.org/10.1038/s41386-021-01228-7}, volume = {47}, year = {2021} } @article{Zillich2022, abstract = {AbstractAlcohol Use Disorder (AUD) is a major contributor to global mortality and morbidity. Postmortem human brain tissue enables the investigation of molecular mechanisms of AUD in the neurocircuitry of addiction. We aimed to identify differentially expressed (DE) genes in the ventral and dorsal striatum between individuals with AUD and controls, and to integrate the results with findings from genome- and epigenome-wide association studies (GWAS/EWAS) to identify functionally relevant molecular mechanisms of AUD. DNA-methylation and gene expression (RNA-seq) data was generated from postmortem brain samples of 48 individuals with AUD and 51 controls from the ventral striatum (VS) and the dorsal striatal regions caudate nucleus (CN) and putamen (PUT). We identified DE genes using DESeq2, performed gene-set enrichment analysis (GSEA), and tested enrichment of DE genes in results of GWASs using MAGMA. Weighted correlation network analysis (WGCNA) was performed for DNA-methylation and gene expression data and gene overlap was tested. Differential gene expression was observed in the dorsal (FDR < 0.05), but not the ventral striatum of AUD cases. In the VS, DE genes at FDR < 0.25 were overrepresented in a recent GWAS of problematic alcohol use. The ARHGEF15 gene was upregulated in all three brain regions. GSEA in CN and VS pointed towards cell-structure associated GO-terms and in PUT towards immune pathways. The WGCNA modules most strongly associated with AUD showed strong enrichment for immune response and inflammation pathways. Our integrated analysis of multi-omics data sets provides further evidence for the importance of immune- and inflammation-related processes in AUD.}, author = {Zillich, Lea and Poisel, Eric and Frank, Josef and Foo, Jerome C. and Friske, Marion M. and Streit, Fabian and Sirignano, Lea and Heilmann-Heimbach, Stefanie and Heimbach, André and Hoffmann, Per and Degenhardt, Franziska and Hansson, Anita C. and Bakalkin, Georgy and Nöthen, Markus M. and Rietschel, Marcella and Spanagel, Rainer and Witt, Stephanie H.}, doi = {10.1038/s41398-022-01959-1}, journal = {Translational Psychiatry}, month = {may}, title = {Multi-omics signatures of alcohol use disorder in the dorsal and ventral striatum}, url = {https://doi.org/10.1038/s41398-022-01959-1}, volume = {12}, year = {2022} }