| 61. |
- 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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| 62. |
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| 63. |
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| 64. |
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| 65. |
- Farahi, A., et al.
(författare)
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Mass variance from archival X-ray properties of Dark Energy Survey Year-1 galaxy clusters
- 2019
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Ingår i: Monthly notices of the Royal Astronomical Society. - : OXFORD UNIV PRESS. - 0035-8711 .- 1365-2966. ; 490:3, s. 3341-3354
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Tidskriftsartikel (refereegranskat)abstract
- Using archival X-ray observations and a lognormal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behaviour of X-ray temperatures, T-X, with optical richness, lambda(RM), for clusters in the redshift range 0.2 < z < 0.7. X-ray temperatures are obtained from Chandra and XMM observations for 58 and 110 redMaPPer systems, respectively. Despite non-uniform sky coverage, the T-X measurements are > 50 per cent complete for clusters with lambda(RM) > 130. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, sigma(ln) (T) (vertical bar) (lambda) = 0.275 +/- 0.019. Joined with constraints for T-X scaling with halo mass from the Weighing the Giants program and richness-temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, sigma(ln) (M) (vertical bar) (lambda) = 0.30 +/- 0.04((stat)) +/- 0.09((sys)), at an optical richness of approximately 100. Uncertainties in external parameters, particularly the slope and variance of the T-X-mass relation and the covariance of T-X and lambda(RM) at fixed mass, dominate the systematic error. The 95 per cent confidence region from joint sample analysis is relatively broad, sigma(ln) (M) (vertical bar) (lambda) is an element of [0.14, 0.55], or a factor 10 in variance.
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| 66. |
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| 67. |
- Ferreira, MA, et al.
(författare)
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Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 1741-
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.
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| 68. |
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| 69. |
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| 70. |
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