Breast cancer risk in relation to urinary and serum biomarkers of phytoestrogen exposure in the European Prospective into Cancer-Norfolk cohort study

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Introduction Phytoestrogens are a group of compounds found in plants that structurally resemble the hormone oestradiol, and thus have the potential to act as oestrogen agonists or antagonists. Their potential effects may alter the risk of breast cancer, but only a limited range of phytoestrogens has been examined in prospective cohort studies. Methods Serum and urine samples from 237 incident breast cancer cases and 952 control individuals (aged 45 to 75 years) in the European Prospective into Cancer-Norfolk cohort were analysed for seven phytoestrogens (daidzein, enterodiol, enterolactone, genistein, glycitein, o-desmethylangolensin, and equol) using liquid chromatography/mass spectrometry. Data on participants' diet, demographics, anthropometrics, and medical history were collected upon recruitment. All models were adjusted for weight, fat and energy intake, family history of breast cancer, social class, analytical batch, and factors related to oestrogen exposure. Results Urinary or serum phytoestrogens were not associated with protection from breast cancer in the European Prospective into Cancer-Norfolk cohort. Breast cancer risk was marginally increased with higher levels of total urinary isoflavones (odds ratio = 1.08 (95% confidence interval = 1.00 to 1.16), P = 0.055); among those with oestrogen receptor-positive tumours, the risk of breast cancer was increased with higher levels of urinary equol (odds ratio = 1.07 (95% confidence interval = 1.01 to 1.12), P = 0.013). Conclusion There was limited evidence of an association between phytoestrogen biomarkers and breast cancer risk in the present study. There was no indication of decreased likelihood of breast cancer with higher levels of phytoestrogen biomarkers, but the observation that some phytoestrogen biomarkers may be associated with greater risk of breast cancer warrants further study with greater statistical power

Accelerated functional brain aging in pre-clinical familial Alzheimer’s disease

Resting state functional connectivity (rs-fMRI) is impaired early in persons who subsequently develop Alzheimer’s disease (AD) dementia. This impairment may be leveraged to aid investigation of the pre-clinical phase of AD. We developed a model that predicts brain age from resting state (rs)-fMRI data, and assessed whether genetic determinants of AD, as well as beta-amyloid (Aβ) pathology, can accelerate brain aging. Using data from 1340 cognitively unimpaired participants between 18–94 years of age from multiple sites, we showed that topological properties of graphs constructed from rs-fMRI can predict chronological age across the lifespan. Application of our predictive model to the context of pre-clinical AD revealed that the pre-symptomatic phase of autosomal dominant AD includes acceleration of functional brain aging. This association was stronger in individuals having significant Aβ pathology

Transitions at CpG Dinucleotides, Geographic Clustering of TP53 Mutations and Food Availability Patterns in Colorectal Cancer

Colorectal cancer is mainly attributed to diet, but the role exerted by foods remains unclear because involved factors are extremely complex. Geography substantially impacts on foods. Correlations between international variation in colorectal cancer-associated mutation patterns and food availabilities could highlight the influence of foods on colorectal mutagenesis. mutations from 12 countries/geographic areas. For food availabilities, we relied on data extracted from the Food Balance Sheets of the Food and Agriculture Organization of the United Nations. Dendrograms for mutation sites, mutation types and food patterns were constructed through Ward's hierarchical clustering algorithm and their stability was assessed evaluating silhouette values. Feature selection used entropy-based measures for similarity between clusterings, combined with principal component analysis by exhaustive and heuristic approaches. hotspots. Pearson's correlation scores, computed between the principal components of the datamatrices for mutation types, food availability and mutation sites, demonstrated statistically significant correlations between transitions at CpGs and both mutation sites and availabilities of meat, milk, sweeteners and animal fats, the energy-dense foods at the basis of “Western” diets. This is best explainable by differential exposure to nitrosative DNA damage due to foods that promote metabolic stress and chronic inflammation