@article{WeberLassalleHaukeRamseretal.2018, author = {Weber-Lassalle, Nana and Hauke, Jan and Ramser, Juliane and Richters, Lisa and Groß, Eva and Bl{\"u}mcke, Britta and Gehrig, Andrea and Kahlert, Anne-Karin and M{\"u}ller, Clemens R. and Hackmann, Karl and Honisch, Ellen and Weber-Lassalle, Konstantin and Niederacher, Dieter and Borde, Julika and Thiele, Holger and Ernst, Corinna and Altm{\"u}ller, Janine and Neidhardt, Guido and N{\"u}rnberg, Peter and Klaschik, Kristina and Schroeder, Christopher and Platzer, Konrad and Volk, Alexander E. and Wang-Gohrke, Shan and Just, Walter and Auber, Bernd and Kubisch, Christian and Schmidt, Gunnar and Horvath, Judit and Wappenschmidt, Barbara and Engel, Christoph and Arnold, Norbert and Dworniczak, Bernd and Rhiem, Kerstin and Meindl, Alfons and Schmutzler, Rita K. and Hahnen, Eric}, title = {BRIP1 loss-of-function mutations confer high risk for familial ovarian cancer, but not familial breast cancer}, series = {Breast Cancer Research}, volume = {20}, journal = {Breast Cancer Research}, doi = {10.1186/s13058-018-0935-9}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-233433}, year = {2018}, abstract = {Background Germline mutations in the BRIP1 gene have been described as conferring a moderate risk for ovarian cancer (OC), while the role of BRIP1 in breast cancer (BC) pathogenesis remains controversial. Methods To assess the role of deleterious BRIP1 germline mutations in BC/OC predisposition, 6341 well-characterized index patients with BC, 706 index patients with OC, and 2189 geographically matched female controls were screened for loss-of-function (LoF) mutations and potentially damaging missense variants. All index patients met the inclusion criteria of the German Consortium for Hereditary Breast and Ovarian Cancer for germline testing and tested negative for pathogenic BRCA1/2 variants. Results BRIP1 LoF mutations confer a high OC risk in familial index patients (odds ratio (OR) = 20.97, 95\% confidence interval (CI) = 12.02-36.57, P < 0.0001) and in the subgroup of index patients with late-onset OC (OR = 29.91, 95\% CI = 14.99-59.66, P < 0.0001). No significant association of BRIP1 LoF mutations with familial BC was observed (OR = 1.81 95\% CI = 1.00-3.30, P = 0.0623). In the subgroup of familial BC index patients without a family history of OC there was also no apparent association (OR = 1.42, 95\% CI = 0.70-2.90, P = 0.3030). In 1027 familial BC index patients with a family history of OC, the BRIP1 mutation prevalence was significantly higher than that observed in controls (OR = 3.59, 95\% CI = 1.43-9.01; P = 0.0168). Based on the negative association between BRIP1 LoF mutations and familial BC in the absence of an OC family history, we conclude that the elevated mutation prevalence in the latter cohort was driven by the occurrence of OC in these families. Compared with controls, predicted damaging rare missense variants were significantly more prevalent in OC (P = 0.0014) but not in BC (P = 0.0693) patients. Conclusions To avoid ambiguous results, studies aimed at assessing the impact of candidate predisposition gene mutations on BC risk might differentiate between BC index patients with an OC family history and those without. In familial cases, we suggest that BRIP1 is a high-risk gene for late-onset OC but not a BC predisposition gene, though minor effects cannot be excluded.}, language = {en} } @article{NaglerNaegeleGillietal.2018, author = {Nagler, Matthias and N{\"a}gele, Thomas and Gilli, Christian and Fragner, Lena and Korte, Arthur and Platzer, Alexander and Farlow, Ashley and Nordborg, Magnus and Weckwerth, Wolfram}, title = {Eco-Metabolomics and Metabolic Modeling: Making the Leap From Model Systems in the Lab to Native Populations in the Field}, series = {Frontiers in Plant Science}, volume = {9}, journal = {Frontiers in Plant Science}, number = {1556}, issn = {1664-462X}, doi = {10.3389/fpls.2018.01556}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-189560}, year = {2018}, abstract = {Experimental high-throughput analysis of molecular networks is a central approach to characterize the adaptation of plant metabolism to the environment. However, recent studies have demonstrated that it is hardly possible to predict in situ metabolic phenotypes from experiments under controlled conditions, such as growth chambers or greenhouses. This is particularly due to the high molecular variance of in situ samples induced by environmental fluctuations. An approach of functional metabolome interpretation of field samples would be desirable in order to be able to identify and trace back the impact of environmental changes on plant metabolism. To test the applicability of metabolomics studies for a characterization of plant populations in the field, we have identified and analyzed in situ samples of nearby grown natural populations of Arabidopsis thaliana in Austria. A. thaliana is the primary molecular biological model system in plant biology with one of the best functionally annotated genomes representing a reference system for all other plant genome projects. The genomes of these novel natural populations were sequenced and phylogenetically compared to a comprehensive genome database of A. thaliana ecotypes. Experimental results on primary and secondary metabolite profiling and genotypic variation were functionally integrated by a data mining strategy, which combines statistical output of metabolomics data with genome-derived biochemical pathway reconstruction and metabolic modeling. Correlations of biochemical model predictions and population-specific genetic variation indicated varying strategies of metabolic regulation on a population level which enabled the direct comparison, differentiation, and prediction of metabolic adaptation of the same species to different habitats. These differences were most pronounced at organic and amino acid metabolism as well as at the interface of primary and secondary metabolism and allowed for the direct classification of population-specific metabolic phenotypes within geographically contiguous sampling sites.}, language = {en} }