9 research outputs found
A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers
Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10−8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers
A comparison of the risks of venous thromboembolic disease in association with different combined oral contraceptives
AimsIn October 1995 in response to the results of three studies, the Committee on the Safety of Medicines advised doctors and pharmacists that oral contraceptives containing desogestrel (DSG) and gestodene (GST) were associated with around a two-fold increase in the risk of thromboembolism compared with those containing other progestogens. The objective of this study was to estimate the risk of idiopathic venous thromboembolic disease (VTE) in users of combined oral contraceptives (COCs), to compare the risk between formulations and to examine the effect of using age banding as opposed to matching by exact year of birth.MethodsA nested case control study was conducted using the General Practice Research Database. Women with a VTE event recorded between 1992 and 1997, who were treated with an anticoagulant, from consideration of their prescription records were likely to have been using a COC prescription on the day of the event and also had no exclusion factors, were deemed cases. For comparison with the previous studies, two nested case control studies were undertaken. Study 1 used controls matched by practice and year of birth. Study 2 used controls matched by practice and within 5 years age bands.ResultsWe found an incidence of idiopathic VTE amongst users of combined oral contraceptives of 3.8 per 10 000 exposed women years. Incidence rates increased markedly after 35 years of age. The nested case-control study using controls matched by year of birth showed no significant difference in risk between the major COC formulations. With levonorgestrel (LNG) 150 µg and ethinyloestradiol (EE) 30 µg as the reference, the adjusted ORs for GST 75 µg and EE 30 µg was 1.3 (95% CI 0.8, 2.1), for DSG 150 µg and EE 30 µg it was 1.0 (95% CI 0.7, 1.7) and for DSG 150 µg and EE 20 µg it was 0.8 (95% CI 0.4, 1.6). Using less rigorous matching criteria, matching controls to cases within 5 years age bands, the ORs increased. When a mixed group of COCs, characterized by having LNG as the progestogen component was used as the reference category, there was an elevation in the ORs for the newer products. We found a significant association between idiopathic VTE and current smoking (OR 2.0 (1.4, 2.7)), BMI over 35 (OR 3.8 (1.8, 8.0)) and asthma (OR 1.9 (1.3, 2.9)). The OR for women who had proxy evidence of general ill health (indicated by the number of prescriptions issued) was 2.2 (1.7, 3.7).ConclusionsThe results of this study indicate that a number of the characteristics of the women taking COCs affect the risk of VTE. There is no evidence to support the hypothesis that there is any difference in risk between COC formulations containing under 50 µg ethinyloestradiol
A genome-wide association scan (GWAS) for mean telomere length within the COGS project: Identified loci show little association with hormone-related cancer risk
Mean telomere length (TL) in blood cells is heritable and has been reported to be associated with risks of several diseases, including cancer. We conducted a meta-analysis of three GWAS for TL (total n=2240) and selected 1629 variants for replication via the "iCOGS" custom genotyping array. All ~200 000 iCOGS variants were analysed with TL, and those displaying associations in healthy controls (n = 15 065) were further tested in breast cancer cases (n = 11 024). We found a novel TL association (Ptrend < 4 × 10-10) at 3p14.4 close to PXK and evidence (Ptrend < 7 × 10-7) for TL loci at 6p22.1 (ZNF311) and 20q11.2 (BCL2L1). We additionally confirmed (Ptrend < 5 × 10-14) the previously reported loci at 3q26.2 (TERC), 5p15.3 (TERT) and 10q24.3 (OBFC1) and found supportive evidence (Ptrend < 5 × 10-4) for the published loci at 2p16.2 (ACYP2), 4q32.2 (NAF1) and 20q13.3 (RTEL1). SNPs tagging these loci explain TL differences of up to 731 bp (corresponding to 18% of total TL in healthy individuals), however, they display little direct evidence for association with breast, ovarian or prostate cancer risks
Facial emotion perception impairments in schizophrenia patients with comorbid antisocial personality disorder
Polygenic risk modeling for prediction of epithelial ovarian cancer risk
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.Genome Instability and Cance
Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes
International audienceGenome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes