@article{HeilingKnuttiScherretal.2021, author = {Heiling, Sven and Knutti, Nadine and Scherr, Franziska and Geiger, J{\"o}rg and Weikert, Juliane and Rose, Michael and Jahns, Roland and Ceglarek, Uta and Scherag, Andr{\´e} and Kiehntopf, Michael}, title = {Metabolite ratios as quality indicators for pre-analytical variation in serum and EDTA plasma}, series = {Metabolites}, volume = {11}, journal = {Metabolites}, number = {9}, issn = {2218-1989}, doi = {10.3390/metabo11090638}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-246261}, year = {2021}, abstract = {In clinical diagnostics and research, blood samples are one of the most frequently used materials. Nevertheless, exploring the chemical composition of human plasma and serum is challenging due to the highly dynamic influence of pre-analytical variation. A prominent example is the variability in pre-centrifugation delay (time-to-centrifugation; TTC). Quality indicators (QI) reflecting sample TTC are of utmost importance in assessing sample history and resulting sample quality, which is essential for accurate diagnostics and conclusive, reproducible research. In the present study, we subjected human blood to varying TTCs at room temperature prior to processing for plasma or serum preparation. Potential sample QIs were identified by Ultra high pressure liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) based metabolite profiling in samples from healthy volunteers (n = 10). Selected QIs were validated by a targeted MS/MS approach in two independent sets of samples from patients (n = 40 and n = 70). In serum, the hypoxanthine/guanosine (HG) and hypoxanthine/inosine (HI) ratios demonstrated high diagnostic performance (Sensitivity/Specificity > 80\%) for the discrimination of samples with a TTC > 1 h. We identified several eicosanoids, such as 12-HETE, 15-(S)-HETE, 8-(S)-HETE, 12-oxo-HETE, (±)13-HODE and 12-(S)-HEPE as QIs for a pre-centrifugation delay > 2 h. 12-HETE, 12-oxo-HETE, 8-(S)-HETE, and 12-(S)-HEPE, and the HI- and HG-ratios could be validated in patient samples.}, language = {en} } @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} }