TY  - JOUR
A1  - Schulz, Herbert
A1  - Ruppert, Ann-Kathrin
A1  - Herms, Stefan
A1  - Wolf, Christiane
A1  - Mirza-Schreiber, Nazanin
A1  - Stegle, Oliver
A1  - Czamara, Darina
A1  - Forstner, Andreas J.
A1  - Sivalingam, Sugirthan
A1  - Schoch, Susanne
A1  - Moebus, Susanne
A1  - Pütz, Benno
A1  - Hillmer, Axel
A1  - Fricker, Nadine
A1  - Vatter, Hartmut
A1  - Müller-Myhsok, Bertram
A1  - Nöthen, Markus M.
A1  - Becker, Albert J.
A1  - Hoffmann, Per
A1  - Sander, Thomas
A1  - Cichon, Sven
T1  - Genome-wide mapping of genetic determinants influencing DNA methylation and gene expression in human hippocampus
JF  - Nature Communications
N2  - 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.
KW  - psychiatry
KW  - epigenetics in the nervous system
KW  - epigenomics
KW  - gene expression
KW  - neurological disorders
Y1  - 2017
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-173168
VL  - 8
ER  - 
TY  - JOUR
A1  - Ziegler, Georg C.
A1  - Radtke, Franziska
A1  - Vitale, Maria Rosaria
A1  - Preuße, André
A1  - Klopocki, Eva
A1  - Herms, Stefan
A1  - Lesch, Klaus-Peter
T1  - Generation of multiple human iPSC lines from peripheral blood mononuclear cells of two SLC2A3 deletion and two SLC2A3 duplication carriers
JF  - Stem Cell Research
N2  - Copy number variants of SLC2A3, which encodes the glucose transporter GLUT3, are associated with several neuropsychiatric and cardiac diseases. Here, we report the successful reprogramming of peripheral blood mononuclear cells from two SLC2A3 duplication and two SLC2A3 deletion carriers and subsequent generation of two transgene-free iPSC clones per donor by Sendai viral transduction. All eight clones represent bona fide hiPSCs with high expression of pluripotency genes, ability to differentiate into cells of all three germ layers and normal karyotype. The generated cell lines will be helpful to enlighten the role of glucometabolic alterations in pathophysiological processes shared across organ boundaries.
KW  - congenital heart-deffects
KW  - transporter gene SLC2A3
KW  - copy-number variation
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-264696
VL  - 56
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  -