Weight gain after diagnosis of breast cancer is associated with higher all-cause mortality rates compared with maintaining body weight. Adverse effects are greater for weight gains of 10.0% or higher.

Obesity is associated with a higher risk of breast cancer mortality. The gold standard approach to weight loss is in-person counseling, but telephone counseling may be more feasible. We examined the effect of in-person versus telephone weight loss counseling versus usual care on 6-month changes in body composition, physical activity, diet, and serum biomarkers. MethodsOne hundred breast cancer survivors with a body mass index $ 25 kg/m 2 were randomly assigned to in-person counseling (n = 33), telephone counseling (n = 34), or usual care (UC) (n = 33). In-person and telephone counseling included 11 30-minute counseling sessions over 6 months. These focused on reducing caloric intake, increasing physical activity, and behavioral therapy. Body composition, physical activity, diet, and serum biomarkers were measured at baseline and 6 months. ResultsThe mean age of participants was 59 6 7.5 years old, with a mean BMI of 33.1 6 6.6 kg/m 2 , and the mean time from diagnosis was 2.9 6 2.1 years. Fifty-one percent of the participants had stage I breast cancer. Average 6-month weight loss was 6.4%, 5.4%, and 2.0% for in-person, telephone, and UC groups, respectively (P = .004, P = .009, and P = .46 comparing in-person with UC, telephone with UC, and in-person with telephone, respectively). A significant 30% decrease in C-reactive protein levels was observed among women randomly assigned to the combined weight loss intervention groups compared with a 1% decrease among women randomly assigned to UC (P = .05). ConclusionBoth in-person and telephone counseling were effective weight loss strategies, with favorable effects on C-reactive protein levels. Our findings may help guide the incorporation of weight loss counseling into breast cancer treatment and care.

Background: Healthy dietary patterns that conform to national dietary guidelines are related to lower chronic disease incidence and longer life span. However, the precise mechanisms involved are unclear. Identifying biomarkers of dietary patterns may provide tools to validate diet quality measurement and determine underlying metabolic pathways influenced by diet quality. Objective: The objective of this study was to examine the correlation of 4 diet quality indexes [the Healthy Eating Index (HEI) 2010, the Alternate Mediterranean Diet Score (aMED), the WHO Healthy Diet Indicator (HDI), and the Baltic Sea Diet (BSD)] with serum metabolites. Design: We evaluated dietary patterns and metabolites in male Finnish smokers (n = 1336) from 5 nested case-control studies within the AlphaTocopherol, Beta-Carotene Cancer Prevention Study cohort. Participants completed a validated food-frequency questionnaire and provided a fasting serum sample before study randomization (1985)(1986)(1987)(1988). Metabolites were measured with the use of mass spectrometry. We analyzed cross-sectional partial correlations of 1316 metabolites with 4 diet quality indexes, adjusting for age, body mass index, smoking, energy intake, education, and physical activity. We pooled estimates across studies with the use of fixed-effects meta-analysis with Bonferroni correction for multiple comparisons, and conducted metabolic pathway analyses. Results: The HEI-2010, aMED, HDI, and BSD were associated with 23, 46, 23, and 33 metabolites, respectively (17, 21, 11, and 10 metabolites, respectively, were chemically identified; r-range: 20.30 to 0.20; P = 6 3 10 215 to 8 3 10 26 ). Food-based diet indexes (HEI-2010, aMED, and BSD) were associated with metabolites correlated with most components used to score adherence (e.g., fruit, vegetables, whole grains, fish, and unsaturated fat). HDI correlated with metabolites related to polyunsaturated fat and fiber components, but not other macro-or micronutrients (e.g., percentages of protein and cholesterol). The lysolipid and food and plant xenobiotic pathways were most strongly associated with diet quality.Conclusions: Diet quality, measured by healthy diet indexes, is associated with serum metabolites, with the specific metabolite profile of each diet index related to the diet components used to score adherence. This trial was registered at clinicaltrials.gov as NCT00342992. Am J Clin Nutr 2017;105:450-65.

Aims/hypothesis We sought to evaluate if the cellular localisation and molecular species of diacylglycerol (DAG) were related to insulin sensitivity in human skeletal muscle. Methods Healthy sedentary obese controls (Ob; n=6; mean±SEM age 39.5±2.3 years; mean±SEM BMI 33.3±1.4 kg/m2), individuals with type 2 diabetes (T2D; n=6; age 44±1.8 years; BMI 30.1±2.3 kg/m2), and lean endurance-trained athletes (Ath; n=10; age 35.4±3.1 years; BMI 23.3±0.8 kg/m2) were studied. Insulin sensitivity was determined using an IVGTT. Muscle biopsy specimens were taken after an overnight fast, fractionated using ultracentrifugation, and DAG species measured using liquid chromatography/MS/MS. Results Total muscle DAG concentration was higher in the Ob (mean±SEM 13.3±1.0 pmol/μg protein) and T2D (15.2±1.0 pmol/μg protein) groups than the Ath group (10.0±0.78 pmol/μg protein, p=0.002). The majority (76-86%) DAG was localised in the membrane fraction for all groups, but was lowest in the Ath group (Ob, 86.2±0.98%; T2D, 84.2±1.2%; Ath, 75.9±2.7%; p=0.008). There were no differences in cytoplasmic DAG species (p>0.12). Membrane DAG species C18:0/C20:4, Di-C16:0 and Di-C18:0 were significantly more abundant in the T2D group. Cytosolic DAG species were negatively related to activation of protein kinase C (PKC)ε but not PKCθ, whereas membrane DAG species were positively related to activation of PKCε, but not PKCθ. Only total membrane DAG (r=−0.624, p=0.003) and Di-C18:0 (r=−0.595, p=0.004) correlated with insulin sensitivity. Disaturated DAG species were significantly lower in the Ath group (p=0.001), and significantly related to insulin sensitivity (r=−0.642, p=0.002). Conclusions/interpretation These data indicate that both cellular localisation and composition of DAG influence the relationship to insulin sensitivity. Our results suggest that only saturated DAG in skeletal muscle membranes are related to insulin resistance in humans.

BACKGROUND.Ceramides are sphingolipids that play causative roles in diabetes and heart disease, with their serum levels measured clinically as biomarkers of cardiovascular disease (CVD). METHODS.We performed targeted lipidomics on serum samples from individuals with familial coronary artery disease (CAD) (n = 462) and population-based controls (n = 212) to explore the relationship between serum sphingolipids and CAD, using unbiased machine learning to identify sphingolipid species positively associated with CAD. RESULTS.Nearly every sphingolipid measured (n = 30 of 32) was significantly elevated in subjects with CAD compared with measurements in population controls. We generated a novel sphingolipid-inclusive CAD risk score, termed SIC, that demarcates patients with CAD independently and more effectively than conventional clinical CVD biomarkers including serum LDL cholesterol and triglycerides. This new metric comprises several minor lipids that likely serve as measures of flux through the ceramide biosynthesis pathway rather than the abundant deleterious ceramide species that are included in other ceramide-based scores. CONCLUSION.This study validates serum ceramides as candidate biomarkers of CVD and suggests that comprehensive sphingolipid panels should be considered as measures of CVD.