ORCID Profile
0000-0001-7339-0570
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Publisher: Springer Science and Business Media LLC
Date: 27-03-2017
DOI: 10.1038/NG.3826
Publisher: Springer Science and Business Media LLC
Date: 28-10-2016
Publisher: Springer Science and Business Media LLC
Date: 02-2012
DOI: 10.1186/BCR3121
Publisher: Public Library of Science (PLoS)
Date: 27-07-2016
Publisher: Wiley
Date: 07-02-2019
DOI: 10.1002/IJC.32114
Publisher: BMJ
Date: 27-05-2005
Publisher: Springer Science and Business Media LLC
Date: 09-02-2016
Publisher: Springer Science and Business Media LLC
Date: 27-04-2016
DOI: 10.1038/NCOMMS11375
Abstract: Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations ( P × 10 −8 ) with oestrogen receptor (ER)-negative breast cancer and BRCA1 -associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5 , a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations ( P .05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
Publisher: Cold Spring Harbor Laboratory
Date: 02-12-2020
DOI: 10.1101/2020.11.30.20219220
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 in idual 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 ancestry 7,669 women of East Asian ancestry 1,072 women of African ancestry, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestry. 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 ancestry 1.14(95%CI:1.08–1.19,AUC:0.538) in women of East Asian ancestry 1.38(95%CI:1.21-1.58,AUC:0.593) in women of African ancestry hazard ratios of 1.37(95%CI:1.30–1.44,AUC:0.592) in BRCA1 pathogenic variant carriers and 1.51(95%CI:1.36-1.67,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.
Publisher: Hindawi Limited
Date: 09-2019
DOI: 10.1002/HUMU.23818
Publisher: Springer Science and Business Media LLC
Date: 12-01-2015
DOI: 10.1038/NG.3185
Publisher: Hindawi Limited
Date: 03-11-2011
DOI: 10.1002/HUMU.21628
Publisher: Public Library of Science (PLoS)
Date: 04-2015
Publisher: Springer Science and Business Media LLC
Date: 11-11-2016
Publisher: Springer Science and Business Media LLC
Date: 29-02-2016
DOI: 10.1038/NG.3521
Publisher: American Medical Association (AMA)
Date: 07-04-2015
Publisher: Springer Science and Business Media LLC
Date: 21-06-2016
Publisher: Springer Science and Business Media LLC
Date: 25-04-2015
Publisher: Elsevier BV
Date: 05-2016
Location: Spain
No related grants have been discovered for orland diez.