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Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10−16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10−6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.
BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7 x 10(-8), HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4 x 10(-8), HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4 x 10(-8), HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2 x 10(-4)). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%-50% compared to 81%-100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.
Cerebellar granule cell (CGC) apoptosis by trophic/potassium (TK) deprivation is a model of election to study the interplay of pro-apoptotic and pro-survival signaling pathways in neuronal cell death. In this model, the c-Jun N-terminal kinase (JNK) induces pro-apoptotic genes through the c-Jun/activator protein 1 (AP-1) transcription factor. On the other side, a survival pathway initiated by lithium leads to repression of pro-apoptotic c-Jun/AP-1 target genes without interfering with JNK activity. Yet, the mechanism by which lithium inhibits c-Jun activity remains to be elucidated. Here, we used this model system to study the regulation and function of site-specific c-Jun phosphorylation at the S63 and T91/T93 JNK sites in neuronal cell death. We found that TK-deprivation led to c-Jun multiphosphorylation at all three JNK sites. However, immunofluorescence analysis of c-Jun phosphorylation at single cell level revealed that the S63 site was phosphorylated in all c-Jun-expressing cells, whereas the response of T91/T93 phosphorylation was more sensitive, mirroring the switch-like apoptotic response of CGCs. Conversely, lithium prevented T91T93 phosphorylation and cell death without affecting the S63 site, suggesting that T91T93 phosphorylation triggers c-Jun pro-apoptotic activity. Accordingly, a c-Jun mutant lacking the T95 priming site for T91/93 phosphorylation protected CGCs from apoptosis, whereas it was able to induce neurite outgrowth in PC12 cells. Vice versa, a c-Jun mutant bearing aspartate substitution of T95 overwhelmed lithium-mediate protection of CGCs from TK-deprivation, validating that inhibition of T91/T93/T95 phosphorylation underlies the effect of lithium on cell death. Mass spectrometry analysis confirmed multiphosphorylation of c-Jun at T91/T93/T95 in cells. Moreover, JNK phosphorylated recombinant c-Jun at T91/T93 in a T95-dependent manner. On the basis of our results, we propose that T91/T93/T95 multiphosphorylation of c-Jun functions as a sensitivity amplifier of the JNK cascade, setting the threshold for c-Jun pro-apoptotic activity in neuronal cells.