Prediction of breast cancer risk based on profiling with common genetic variants

BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.

Board attributes that increase firm risk - evidence from the UK

Purpose – The aim of the paper is to identify the board attributes that significantly increase firm risk. The study aims to find if board size, percentage of non-executive directors, women on the board, a powerful CEO, equity ownership amongst executive board directors and institutional investor ownership, are associated with firm risk. This is the first study that examines which board attributes increase firm risk using a UK based sample. Design/methodology/approach – This empirical study collected secondary data from Bloomberg and Morningstar databases. The data sample is an unbalanced panel of 260 companies’ secondary data on FTSE 350 index in the UK, from 2005 to 2010. The data was statistically analysed using STATA. Findings – The study establishes the board attributes that were significantly related to firm risk. The results show that a board which can increase firm risk is one that is small in size,has high equity ownership amongst executive board directors and has high institutional investor ownership. Research limitations/implications – The governance culture and regulatory system in the UK is different from other countries. Since the data is a UK based sample, the results can lack generalisability. Practical implications – The results are useful for investors who invest in large firms, to have the knowledge about the board attributes that can increase firm risk. Regulators can also use the results to strengthen regulatory guidelines. Originality/value – This study fills the gap in knowledge in UK governance literature on the board attributes that can increase firm risk.