@article{HavikDegenhardtJohanssonetal.2012,
  author    = {Havik, Bjarte and Degenhardt, Franziska A. and Johansson, Stefan and Fernandes, Carla P. D. and Hinney, Anke and Scherag, Andr{\´e} and Lybaek, Helle and Djurovic, Srdjan and Christoforou, Andrea and Ersland, Kari M. and Giddaluru, Sudheer and O'Donovan, Michael C. and Owen, Michael J. and Craddock, Nick and M{\"u}hleisen, Thomas W. and Mattheisen, Manuel and Schimmelmann, Benno G. and Renner, Tobias and Warnke, Andreas and Herpertz-Dahlmann, Beate and Sinzig, Judith and Albayrak, {\"O}zg{\"u}r and Rietschel, Marcella and N{\"o}then, Markus M. and Bramham, Clive R. and Werge, Thomas and Hebebrand, Johannes and Haavik, Jan and Andreassen, Ole A. and Cichon, Sven and Steen, Vidar M. and Le Hellard, Stephanie},
  title     = {DCLK1 Variants Are Associated across Schizophrenia and Attention Deficit/Hyperactivity Disorder},
  series = {PLoS One},
  volume    = {7},
  journal   = {PLoS One},
  number    = {4},
  doi       = {10.1371/journal.pone.0035424},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-135285},
  pages     = {e35424},
  year      = {2012},
  abstract  = {Doublecortin and calmodulin like kinase 1 (DCLK1) is implicated in synaptic plasticity and neurodevelopment. Genetic variants in DCLK1 are associated with cognitive traits, specifically verbal memory and general cognition. We investigated the role of DCLK1 variants in three psychiatric disorders that have neuro-cognitive dysfunctions: schizophrenia (SCZ), bipolar affective disorder (BP) and attention deficit/hyperactivity disorder (ADHD). We mined six genome wide association studies (GWASs) that were available publically or through collaboration; three for BP, two for SCZ and one for ADHD. We also genotyped the DCLK1 region in additional samples of cases with SCZ, BP or ADHD and controls that had not been whole-genome typed. In total, 9895 subjects were analysed, including 5308 normal controls and 4,587 patients (1,125 with SCZ, 2,496 with BP and 966 with ADHD). Several DCLK1 variants were associated with disease phenotypes in the different samples. The main effect was observed for rs7989807 in intron 3, which was strongly associated with SCZ alone and even more so when cases with SCZ and ADHD were combined (P-value = 4x10\(^{-5}\) and 4x10\(^{-6}\), respectively). Associations were also observed with additional markers in intron 3 (combination of SCZ, ADHD and BP), intron 19 (SCZ+BP) and the 3'UTR (SCZ+BP). Our results suggest that genetic variants in DCLK1 are associated with SCZ and, to a lesser extent, with ADHD and BP. Interestingly the association is strongest when SCZ and ADHD are considered together, suggesting common genetic susceptibility. Given that DCLK1 variants were previously found to be associated with cognitive traits, these results are consistent with the role of DCLK1 in neurodevelopment and synaptic plasticity.},
  language  = {en}
}
@article{MarenholzEsparzaGordilloRueschendorfetal.2015,
  author    = {Marenholz, Ingo and Esparza-Gordillo, Jorge and R{\"u}schendorf, Franz and Bauerfeind, Anja and Strachan, David P. and Spycher, Ben D. and Baurecht, Hansj{\"o}rg and Magaritte-Jeannin, Patricia and S{\"a}{\"a}f, Annika and Kerkhof, Marjan and Ege, Markus and Baltic, Svetlana and Matheson, Melanie C. and Li, Jin and Michel, Sven and Ang, Wei Q. and McArdle, Wendy and Arnold, Andreas and Homuth, Georg and Demenais, Florence and Bouzigon, Emmanuelle and S{\"o}derh{\"a}ll, Cilla and Pershagen, G{\"o}ran and de Jongste, Johan C. and Postma, Dirkje S. and Braun-Fahrl{\"a}nder, Charlotte and Horak, Elisabeth and Ogorodova, Ludmila M. and Puzyrev, Valery P. and Bragina, Elena Yu and Hudson, Thomas J. and Morin, Charles and Duffy, David L. and Marks, Guy B. and Robertson, Colin F. and Montgomery, Grant W. and Musk, Bill and Thompson, Philip J. and Martin, Nicholas G. and James, Alan and Sleiman, Patrick and Toskala, Elina and Rodriguez, Elke and F{\"o}lster-Holst, Regina and Franke, Andre and Lieb, Wolfgang and Gieger, Christian and Heinzmann, Andrea and Rietschel, Ernst and Keil, Thomas and Cichon, Sven and N{\"o}then, Markus M. and Pennel, Craig E. and Sly, Peter D. and Schmidt, Carsten O. and Matanovic, Anja and Schneider, Valentin and Heinig, Matthias and H{\"u}bner, Norbert and Holt, Patrick G. and Lau, Susanne and Kabesch, Michael and Weidinger, Stefan and Hakonarson, Hakon and Ferreira, Manuel A. R. and Laprise, Catherine and Freidin, Maxim B. and Genuneit, Jon and Koppelman, Gerard H. and Mel{\´e}n, Erik and Dizier, Marie-H{\´e}l{\`e}ne and Henderson, A. John and Lee, Young Ae},
  title     = {Meta-analysis identifies seven susceptibility loci involved in the atopic march},
  series = {Nature Communications},
  volume    = {6},
  journal   = {Nature Communications},
  number    = {8804},
  doi       = {10.1038/ncomms9804},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-139835},
  year      = {2015},
  abstract  = {Eczema often precedes the development of asthma in a disease course called the 'atopic march'. To unravel the genes underlying this characteristic pattern of allergic disease, we conduct a multi-stage genome-wide association study on infantile eczema followed by childhood asthma in 12 populations including 2,428 cases and 17,034 controls. Here we report two novel loci specific for the combined eczema plus asthma phenotype, which are associated with allergic disease for the first time; rs9357733 located in EFHC1 on chromosome 6p12.3 (OR 1.27; P = 2.1 x 10(-8)) and rs993226 between TMTC2 and SLC6A15 on chromosome 12q21.3 (OR 1.58; P = 5.3 x 10(-9)). Additional susceptibility loci identified at genome-wide significance are FLG (1q21.3), IL4/KIF3A (5q31.1), AP5B1/OVOL1 (11q13.1), C11orf30/LRRC32 (11q13.5) and IKZF3 (17q21). We show that predominantly eczema loci increase the risk for the atopic march. Our findings suggest that eczema may play an important role in the development of asthma after eczema.},
  language  = {en}
}
@article{MitchellLiWeinholdetal.2016,
  author    = {Mitchell, Jonathan S. and Li, Ni and Weinhold, Niels and F{\"o}rsti, Asta and Ali, Mina and van Duin, Mark and Thorleifsson, Gudmar and Johnson, David C. and Chen, Bowang and Halvarsson, Britt-Marie and Gudbjartsson, Daniel F. and Kuiper, Rowan and Stephens, Owen W. and Bertsch, Uta and Broderick, Peter and Campo, Chiara and Einsele, Hermann and Gregory, Walter A. and Gullberg, Urban and Henrion, Marc and Hillengass, Jens and Hoffmann, Per and Jackson, Graham H. and Johnsson, Ellinor and J{\"o}ud, Magnus and Kristinsson, Sigurdur Y. and Lenhoff, Stig and Lenive, Oleg and Mellqvist, Ulf-Henrik and Migliorini, Gabriele and Nahi, Hareth and Nelander, Sven and Nickel, Jolanta and N{\"o}then, Markus M. and Rafnar, Thorunn and Ross, Fiona M. and da Silva Filho, Miguel Inacio and Swaminathan, Bhairavi and Thomsen, Hauke and Turesson, Ingemar and Vangsted, Annette and Vogel, Ulla and Waage, Anders and Walker, Brian A. and Wihlborg, Anna-Karin and Broyl, Annemiek and Davies, Faith E. and Thorsteinsdottir, Unnur and Langer, Christian and Hansson, Markus and Kaiser, Martin and Sonneveld, Pieter and Stefansson, Kari and Morgan, Gareth J. and Goldschmidt, Hartmut and Hemminki, Kari and Nilsson, Bj{\"o}rn and Houlston, Richard S.},
  title     = {Genome-wide association study identifies multiple susceptibility loci for multiple myeloma},
  series = {Nature Communications},
  volume    = {7},
  journal   = {Nature Communications},
  doi       = {10.1038/ncomms12050},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-165983},
  pages     = {12050},
  year      = {2016},
  abstract  = {Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P=1.31 × 10-8), 6q21 (rs9372120, P=9.09 × 10-15), 7q36.1 (rs7781265, P=9.71 × 10-9), 8q24.21 (rs1948915, P=4.20 × 10-11), 9p21.3 (rs2811710, P=1.72 × 10-13), 10p12.1 (rs2790457, P=1.77 × 10-8), 16q23.1 (rs7193541, P=5.00 × 10-12) and 20q13.13 (rs6066835, P=1.36 × 10-13), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.},
  language  = {en}
}
@article{SchulzRuppertHermsetal.2017,
  author    = {Schulz, Herbert and Ruppert, Ann-Kathrin and Herms, Stefan and Wolf, Christiane and Mirza-Schreiber, Nazanin and Stegle, Oliver and Czamara, Darina and Forstner, Andreas J. and Sivalingam, Sugirthan and Schoch, Susanne and Moebus, Susanne and P{\"u}tz, Benno and Hillmer, Axel and Fricker, Nadine and Vatter, Hartmut and M{\"u}ller-Myhsok, Bertram and N{\"o}then, Markus M. and Becker, Albert J. and Hoffmann, Per and Sander, Thomas and Cichon, Sven},
  title     = {Genome-wide mapping of genetic determinants influencing DNA methylation and gene expression in human hippocampus},
  series = {Nature Communications},
  volume    = {8},
  journal   = {Nature Communications},
  doi       = {10.1038/s41467-017-01818-4},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-173168},
  year      = {2017},
  abstract  = {Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the \(cis\)-regulatory effects of single-nucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify \(cis\)-meQTLs at 14,118 CpG methylation sites and \(cis\)-eQTLs for 302 3′-mRNA transcripts of 288 genes. Hippocampal \(cis\)-meQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. \(Cis\)-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of \(cis\)-acting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders.},
  language  = {en}
}
@article{BreuerMattheisenFranketal.2018,
  author    = {Breuer, Ren{\´e} and Mattheisen, Manuel and Frank, Josef and Krumm, Bertram and Treutlein, Jens and Kassem, Layla and Strohmaier, Jana and Herms, Stefan and M{\"u}hleisen, Thomas W. and Degenhardt, Franziska and Cichon, Sven and N{\"o}then, Markus M. and Karypis, George and Kelsoe, John and Greenwood, Tiffany and Nievergelt, Caroline and Shilling, Paul and Shekhtman, Tatyana and Edenberg, Howard and Craig, David and Szelinger, Szabolcs and Nurnberger, John and Gershon, Elliot and Alliey-Rodriguez, Ney and Zandi, Peter and Goes, Fernando and Schork, Nicholas and Smith, Erin and Koller, Daniel and Zhang, Peng and Badner, Judith and Berrettini, Wade and Bloss, Cinnamon and Byerley, William and Coryell, William and Foroud, Tatiana and Guo, Yirin and Hipolito, Maria and Keating, Brendan and Lawson, William and Liu, Chunyu and Mahon, Pamela and McInnis, Melvin and Murray, Sarah and Nwulia, Evaristus and Potash, James and Rice, John and Scheftner, William and Z{\"o}llner, Sebastian and McMahon, Francis J. and Rietschel, Marcella and Schulze, Thomas G.},
  title     = {Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics},
  series = {International Journal of Bipolar Disorders},
  volume    = {6},
  journal   = {International Journal of Bipolar Disorders},
  doi       = {10.1186/s40345-018-0132-x},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-220509},
  year      = {2018},
  abstract  = {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.},
  language  = {en}
}