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.

25 January 2019 In Cardiovascular System

Coronary artery calcification (CAC) is associated with atherosclerotic complications. However, elevated CAC may not always imply a worse prognosis. Herein, we report the clinical evolution of long-term red wine (RW) drinkers in relation to CAC. We followed 200 healthy male habitual RW drinkers and compared them to 154 abstainers for a period of 5.5 years. The initial evaluation included coronary computed tomography angiography (CTA), clinical, demographics, and laboratory data. CAC was quantified by the Agatston score. The follow-up process was conducted by telephone calls and/or hospital record review. The composite end-point of total death, acute myocardial infarction (AMI), or coronary revascularization (or major adverse cardiac event - MACE) was assessed. The RW drinkers ingested 28.9+/-15 g of alcohol/day for 23.4+/-12.3 years. They had higher high-density lipoprotein and low-density lipoprotein, but lower C-reactive protein than abstainers. Age, total cholesterol, triglycerides, glucose, and liver enzymes were similar. History of diabetes was lower among drinkers, but other risk factors were similar. However, drinkers had higher CAC than abstainers; the mean value was 131.5+/-362 in drinkers vs 40.5+/-320 in abstainers (P<0.001). The median and interquartile range were 15 (0.0-131.5) in RW drinkers and 1 (0.0-40.5) in abstainers (P=0.003). During the follow-up, MACE was significantly lower in drinkers than in abstainers, despite their higher CAC. The difference was driven mainly by AMI (0 vs 6; P<0.03). Greater CAC values in this setting did not predict worse prognosis. A possible underlying mechanism is lesion calcification, which leads to plaque stabilization and less clinical events.

25 January 2019 In General Health

Alcoholic beverages, specifically wine, have been consumed for many years. Wine is postulated to play an important role in the improvement of cardiovascular risk factors. Most epidemiological studies have found sustained consumption at light-to-moderate amounts to increase HDL cholesterol, reduce platelet aggregation, and promote fibrinolysis. Wine consumption has been inversely associated with ischemic heart disease, and the alcohol-blood pressure association, in most studies, follows a J-shaped curve. These outcomes have been attributed to the molecular constituents of wine, namely ethanol and polyphenols. Due to the continued interest in wine as a biological beverage, we review the chemistry of wine as clinicians, including its chemical composition, viticulture and enological practices, and other chemical factors that influence the bioactive components of wine. We also outline the biological effects of wine components and directions for future research.

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