| 1. |
- Aad, G, et al.
(författare)
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- 2015
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swepub:Mat__t
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| 2. |
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| 3. |
- Jiang, X., et al.
(författare)
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Shared heritability and functional enrichment across six solid cancers
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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| 6. |
- Dareng, EO, et al.
(författare)
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Polygenic risk modeling for prediction of epithelial ovarian cancer risk
- 2022
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Ingår i: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
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Tidskriftsartikel (refereegranskat)abstract
- Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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| 7. |
- Feroci, M., et al.
(författare)
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The large observatory for x-ray timing
- 2014
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819496126
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Konferensbidrag (refereegranskat)abstract
- The Large Observatory For x-ray Timing (LOFT) was studied within ESA M3 Cosmic Vision framework and participated in the final downselection for a launch slot in 2022-2024. Thanks to the unprecedented combination of effective area and spectral resolution of its main instrument, LOFT will study the behaviour of matter under extreme conditions, such as the strong gravitational field in the innermost regions of accretion flows close to black holes and neutron stars, and the supranuclear densities in the interior of neutron stars. The science payload is based on a Large Area Detector (LAD, 10 m2 effective area, 2-30 keV, 240 eV spectral resolution, 1° collimated field of view) and a Wide Field Monitor (WFM, 2-50 keV, 4 steradian field of view, 1 arcmin source location accuracy, 300 eV spectral resolution). The WFM is equipped with an on-board system for bright events (e.g. GRB) localization. The trigger time and position of these events are broadcast to the ground within 30 s from discovery. In this paper we present the status of the mission at the end of its Phase A study.
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