26 February 2019 In Cancer

PURPOSE: Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).

METHODS: BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.

RESULTS: Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of >/=17-<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of >/=30% (high risk).

CONCLUSION: This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.

22 February 2019 In Cancer

PURPOSE: Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).

METHODS: BOADICEA incorporates the effects of truncating variants in BRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.

RESULTS: Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of >/=17-<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of >/=30% (high risk).

CONCLUSION: This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.

29 October 2018 In Liver Disease

INTRODUCTION: It is unclear whether low levels of alcohol are harmful in patients with non-alcoholic fatty liver disease (NAFLD). We aimed to determine whether quantity, binge pattern consumption, or type of alcohol was associated with liver fibrosis in patients with NAFLD.

METHODS: Previous and current alcohol consumption was assessed in NAFLD patients undergoing liver biopsy. All subjects currently consumed /=4 standard drinks (female) or >/=5 standard drinks (male) in one sitting. Liver biopsies were scored according to the NASH CRN system with F3/4 fibrosis defined as advanced.

RESULTS: Among 187 patients (24% with advanced fibrosis), the median weekly alcohol consumption was 20 (2.3-60) g over an average of 18 years. Modest consumption (1-70 g per week) was associated with lower mean fibrosis stage compared to lifetime abstainers (p < 0.05) and a decreased risk of advanced fibrosis (OR 0.33, 95% CI 0.14-0.78, p = 0.01). The association with reduced fibrosis was not seen in subjects drinking in a binge-type fashion. Exclusive wine drinkers but not exclusive beer drinkers, had lower mean fibrosis stage and lower odds of advanced fibrosis (OR 0.20, 95% CI 0.06-0.69, p = 0.01), compared to lifetime abstinent subjects. No interaction between gender and alcohol quantity, type, or binge consumption on fibrosis was observed.

DISCUSSION: Modest (1-70 g per week) alcohol consumption, particularly wine in a non-binge pattern, is associated with lower fibrosis in patients with NAFLD. Prospective longitudinal studies into fibrosis progression, cardiovascular outcomes, and mortality are required before clinical recommendations can be made.

29 October 2018 In Cancer

Epidemiological studies have been used to show associations between modifiable lifestyle habits and the incidence of breast cancer. Among such factors, a history of alcohol use has been reported in multiple studies and meta-analyses over the past decades. However, associative epidemiological studies that were interpreted as evidence that even moderate alcohol consumption increases breast cancer incidence have been controversial. In this review, we consider the literature on the relationship between moderate or heavy alcohol use, both in possible biological mechanisms and in variations in susceptibility due to genetic or epigenetic factors. We argue that there is a need to incorporate additional approaches to move beyond the associations that are reported in traditional epidemiological analyses and incorporate information on molecular pathologic signatures as a requirement to posit causal inferences. In particular, we point to the efforts of the transdisciplinary field of molecular pathological epidemiology (MPE) to evaluate possible causal relationships, if any, of alcohol consumption and breast cancer. A wider application of the principles of MPE to this field would constitute a giant step that could enhance our understanding of breast cancer and multiple modifiable risk factors, a step that would be particularly suited to the era of "personalized medicine".

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