@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{HenningsKohliCzamaraetal.2013, author = {Hennings, Johannes M. and Kohli, Martin A. and Czamara, Darina and Giese, Maria and Eckert, Anne and Wolf, Christiane and Heck, Angela and Domschke, Katharina and Arolt, Volker and Baune, Bernhard T. and Horstmann, Sonja and Br{\"u}ckl, Tanja and Klengel, Torsten and Menke, Andreas and M{\"u}ller-Myhsok, Bertram and Ising, Marcus and Uhr, Manfred and Lucae, Susanne}, title = {Possible Associations of NTRK2 Polymorphisms with Antidepressant Treatment Outcome: Findings from an Extended Tag SNP Approach}, series = {PLoS ONE}, volume = {8}, journal = {PLoS ONE}, number = {6}, doi = {10.1371/journal.pone.0065636}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130924}, pages = {e64947}, year = {2013}, abstract = {Background: Data from clinical studies and results from animal models suggest an involvement of the neurotrophin system in the pathology of depression and antidepressant treatment response. Genetic variations within the genes coding for the brain-derived neurotrophic factor (BDNF) and its key receptor Trkb (NTRK2) may therefore influence the response to antidepressant treatment. Methods: We performed a single and multi-marker association study with antidepressant treatment outcome in 398 depressed Caucasian inpatients participating in the Munich Antidepressant Response Signature (MARS) project. Two Caucasian replication samples (N = 249 and N = 247) were investigated, resulting in a total number of 894 patients. 18 tagging SNPs in the BDNF gene region and 64 tagging SNPs in the NTRK2 gene region were genotyped in the discovery sample; 16 nominally associated SNPs were tested in two replication samples. Results: In the discovery analysis, 7 BDNF SNPs and 9 NTRK2 SNPs were nominally associated with treatment response. Three NTRK2 SNPs (rs10868223, rs1659412 and rs11140778) also showed associations in at least one replication sample and in the combined sample with the same direction of effects (\(P_{corr}\) = .018, \(P_{corr}\) = .015 and \(P_{corr}\) = .004, respectively). We observed an across-gene BDNF-NTRK2 SNP interaction for rs4923468 and rs1387926. No robust interaction of associated SNPs was found in an analysis of BDNF serum protein levels as a predictor for treatment outcome in a subset of 93 patients. Conclusions/Limitations: Although not all associations in the discovery analysis could be unambiguously replicated, the findings of the present study identified single nucleotide variations in the BDNF and NTRK2 genes that might be involved in antidepressant treatment outcome and that have not been previously reported in this context. These new variants need further validation in future association studies.}, language = {en} }