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Institute
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.
Motivation
The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.
Main types of variables included
The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.
Spatial location and grain
BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).
Time period and grain
BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.
Major taxa and level of measurement
BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
Software format
.csv and .SQL.