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- Li, Kuanrong, et al.
(author)
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Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts
- 2018
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In: Breast Cancer Research. - : BioMed Central. - 1465-5411 .- 1465-542X. ; 20
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Journal article (peer-reviewed)abstract
- BACKGROUND: Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction.METHODS: We built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women's Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.RESULTS: Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10- 6 for ModelER+ and 3.0 × 10- 6 for ModelGail.CONCLUSIONS: Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.
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| 2. |
- Ward, Heather A., et al.
(author)
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Meat and haem iron intake in relation to glioma in the European Prospective Investigation into Cancer and Nutrition study
- 2018
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In: European Journal of Cancer Prevention. - : Lippincott Williams & Wilkins. - 0959-8278 .- 1473-5709. ; 27:4, s. 379-383
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Journal article (peer-reviewed)abstract
- Diets high in red or processed meat have been associated positively with some cancers, and several possible underlying mechanisms have been proposed, including iron-related pathways. However, the role of meat intake in adult glioma risk has yielded conflicting findings because of small sample sizes and heterogeneous tumour classifications. The aim of this study was to examine red meat, processed meat and iron intake in relation to glioma risk in the European Prospective Investigation into Cancer and Nutrition study. In this prospective cohort study, 408751 individuals from nine European countries completed demographic and dietary questionnaires at recruitment. Multivariable Cox proportional hazards models were used to examine intake of red meat, processed meat, total dietary iron and haem iron in relation to incident glioma. During an average follow-up of 14.1 years, 688 incident glioma cases were diagnosed. There was no evidence that any of the meat variables (red, processed meat or subtypes of meat) or iron (total or haem) were associated with glioma; results were unchanged when the first 2 years of follow-up were excluded. This study suggests that there is no association between meat or iron intake and adult glioma. This is the largest prospective analysis of meat and iron in relation to glioma and as such provides a substantial contribution to a limited and inconsistent literature.
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| 3. |
- Kroeger, Janine, et al.
(author)
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Circulating Fetuin-A and Risk of Type 2 Diabetes : A Mendelian Randomization Analysis
- 2018
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In: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 67:6, s. 1200-1205
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Journal article (peer-reviewed)abstract
- Fetuin-A, a hepatic-origin protein, is strongly positively associated with risk of type 2 diabetes in human observational studies, but it is unknown whether this association is causal. Weaimed to study the potential causal relation of circulating fetuin-A to risk of type 2 diabetes in a Mendelian randomization study with single nucleotide polymorphisms located in the fetuin-A-encoding AHSG gene. We used data from eight European countries of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study including 10,020 incident cases. Plasma fetuin-A concentration was measured in a subset of 965 subcohort participants and 654 case subjects. A genetic score of the AHSG single nucleotide polymorphisms was strongly associated with fetuin-A (28% explained variation). Using the genetic score as instrumental variable of fetuin-A, we observed no significant association of a 50 mu g/mL higher fetuin-A concentration with diabetes risk (hazard ratio 1.02 [95% CI 0.97, 1.07]). Combining our results with those from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (12,171 case subjects) also did not suggest a clear significant relation of fetuin-A with diabetes risk. In conclusion, although there is mechanistic evidence for an effect of fetuin-A on insulin sensitivity and secretion, this study does not support a strong, relevant relationship between circulating fetuin-A and diabetes risk in the general population.
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| 4. |
- Campanella, Gianluca, et al.
(author)
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Epigenome-wide association study of adiposity and future risk of obesity-related diseases
- 2018
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In: International Journal of Obesity. - : Nature Publishing Group. - 0307-0565 .- 1476-5497. ; 42:12, s. 2022-2035
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Journal article (peer-reviewed)abstract
- Background: Obesity is an established risk factor for several common chronic diseases such as breast and colorectal cancer, metabolic and cardiovascular diseases; however, the biological basis for these relationships is not fully understood. To explore the association of obesity with these conditions, we investigated peripheral blood leucocyte (PBL) DNA methylation markers for adiposity and their contribution to risk of incident breast and colorectal cancer and myocardial infarction.Methods: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waistheight ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population.Results: We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P=9.07×10−8 to 3.27×10−18) and lower transcriptional activity of the full-length isoform of ABCG1 (P=6.00×10−7), higher triglyceride levels (P=5.37×10−9) and higher triglycerides-to-HDL cholesterol ratio (P=1.03×10−10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P<1.6×10−3) and one intergenic locus on chromosome 1 was inversely associated with myocardial infarction (P<1.25×10−3), independently of obesity and established risk factors.Conclusion: Our results suggest that epigenetic changes, in particular altered DNA methylation patterns, may be an intermediate biomarker at the intersection of obesity and obesity-related diseases, and could offer clues as to underlying biological mechanisms.
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