The Mediterranean Diet, Cardiometabolic Biomarkers, and Risk of All-Cause Mortality: A 25-Year Follow-Up Study of the Women's Health Study.

Background: Higher consumption of Mediterranean diet (MED) intake has been associated with reduced risk of all-cause mortality but limited data are available examining long-term outcomes in women or the underlying molecular mechanisms of this inverse association in human populations. We aimed to investigate the association of MED intake with long-term risk of all-cause mortality in women and to better characterize the relative contribution of traditional and novel cardiometabolic factors to the MED-related risk reduction in morality. Methods: In a prospective cohort study of 25,315 initially healthy women from the Women's Health Study, we assessed dietary MED intake using a validated semiquantitative food frequency questionnaire according to the usual 9-category measure of MED adherence. Baseline levels of more than thirty cardiometabolic biomarkers were measured using standard assays and targeted nuclear magnetic resonance spectroscopy, including lipids, lipoproteins, apolipoproteins, inflammation, glucose metabolism and insulin resistance, branched-chain amino acids, small metabolites, and clinical factors. Mortality and cause of death was ascertained prospectively through medical and death records. Results: During a mean follow-up of 25 years, 3,879 deaths were ascertained. Compared to the reference group of low MED intake (0-3, approximately the bottom tertile), and adjusting for age, treatment, and energy intake, risk reductions were observed for the middle and upper MED groups with respective HRs of 0.84 (95% CI 0.78-0.90) and 0.77 (95% CI 0.70-0.84), p for trend <0.0001. Further adjusting for smoking, physical activity, alcohol intake and menopausal factors attenuated the risk reductions which remained significant with respective HRs of 0.92 (95% CI 0.85-0.99) and 0.89 (95% CI 0.82-0.98), p for trend 0.0011. Risk reductions were generally similar for CVD and non-CVD mortality. Small molecule metabolites (e.g., alanine and homocysteine) and inflammation made the largest contributions to lower mortality risk (accounting for 14.8% and 13.0% of the benefit of the MED-mortality association, respectively), followed by triglyceride-rich lipoproteins (10.2%), adiposity (10.2%) and insulin resistance (7.4%), with lesser contributions (<3%) from other pathways including branched-chain amino acids, high-density lipoproteins, low-density lipoproteins, glycemic measures, and hypertension. Conclusions: In the large-scale prospective Women's Health Study of 25,315 initially healthy US women followed for 25 years, higher MED intake was associated with approximately one fifth relative risk reduction in mortality. The inverse association was only partially explained by known novel and traditional cardiometabolic factors.

Dietary Pattern Specific Protein Biomarkers for Cardiovascular Disease: A Cross-Sectional Study in 2 Independent Cohorts.

Background Mechanisms related to the influence of diet on the development of cardiovascular disease are not entirely understood, and protein biomarkers may help to understand these pathways. Studies of biomarkers identified with multiplex proteomic methods and dietary patterns are largely lacking. Methods and Results Dietary patterns were generated through principal component analysis in 2 population-based Swedish cohorts, the EpiHealth (EpiHealth study; n=20 817 men and women) and the SMCC (Swedish Mammography Cohort Clinical [n=4650 women]). A set of 184 protein cardiovascular disease biomarkers were measured with 2 high-throughput, multiplex immunoassays. Discovery and replication multivariable linear regression analyses were used to investigate the associations between the principal component analysis-generated dietary patterns and the cardiovascular disease-associated protein biomarkers, first in the EpiHealth (n=2240) and then in the Swedish Mammography Cohort Clinical. Four main dietary patterns were identified in the EpiHealth, and 3 patterns were identified in the Swedish Mammography Cohort Clinical. The healthy and the Western/traditional patterns were found in both cohorts. In the EpiHealth, 57 protein biomarkers were associated with 3 of the dietary patterns, and 41 of these associations were replicated in the Swedish Mammography Cohort Clinical, with effect estimates ranging from 0.057 to 0.083 (P-value range, 5.0×10-2-1.4×10-9) for each SD increase in the relative protein concentration. Independent associations were established between dietary patterns and the 21 protein biomarkers. Two proteins, myeloperoxidase and resistin, were associated with both the healthy and the light meal pattern but in opposite directions. Conclusions We have discovered and replicated independent associations between dietary patterns and 21 biomarkers linked to cardiovascular disease, which have a role in the pathways related to inflammation, endothelial and immune function, cell adhesion, and metabolism.

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study.

AIMS/HYPOTHESIS: We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later. METHODS: Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC. RESULTS: The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age(2) and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity. CONCLUSIONS/INTERPRETATION: These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes.

Physical activity, smoking, and genetic predisposition to obesity in people from Pakistan: the PROMIS study.

BACKGROUND: Multiple genetic variants have been reliably associated with obesity-related traits in Europeans, but little is known about their associations and interactions with lifestyle factors in South Asians. METHODS: In 16,157 Pakistani adults (8232 controls; 7925 diagnosed with myocardial infarction [MI]) enrolled in the PROMIS Study, we tested whether: a) BMI-associated loci, individually or in aggregate (as a genetic risk score--GRS), are associated with BMI; b) physical activity and smoking modify the association of these loci with BMI. Analyses were adjusted for age, age(2), sex, MI (yes/no), and population substructure. RESULTS: Of 95 SNPs studied here, 73 showed directionally consistent effects on BMI as reported in Europeans. Each additional BMI-raising allele of the GRS was associated with 0.04 (SE = 0.01) kg/m(2) higher BMI (P = 4.5 × 10(-14)). We observed nominal evidence of interactions of CLIP1 rs11583200 (P(interaction) = 0.014), CADM2 rs13078960 (P(interaction) = 0.037) and GALNT10 rs7715256 (P(interaction) = 0.048) with physical activity, and PTBP2 rs11165643 (P(interaction) = 0.045), HIP1 rs1167827 (P(interaction) = 0.015), C6orf106 rs205262 (P(interaction) = 0.032) and GRID1 rs7899106 (P(interaction) = 0.043) with smoking on BMI. CONCLUSIONS: Most BMI-associated loci have directionally consistent effects on BMI in Pakistanis and Europeans. There were suggestive interactions of established BMI-related SNPs with smoking or physical activity.

The lysine specific demethylase-1 (LSD1/KDM1A) regulates VEGF-A expression in prostate cancer.

Recurrent prostate cancer remains a major clinical challenge. The lysine specific demethylase-1 (LSD1/KDM1A), together with the JmjC domain-containing JMJD2A and JMJD2C proteins, have emerged as critical regulators of histone lysine methylation. The LSD1-JMJD2 complex functions as a transcriptional co-regulator of hormone activated androgen and estrogen receptors at specific gene promoters. LSD1 also regulates DNA methylation and p53 function. LSD1 is overexpressed in numerous cancers including prostate cancer through an unknown mechanism. We investigated expression of the LSD1 and JMJD2A in malignant human prostate specimens. We correlated LSD1 and JMJD2A expression with known mediators of prostate cancer progression: VEGF-A and cyclin A1. We show that elevated expression of LSD1, but not JMJD2A, correlates with prostate cancer recurrence and with increased VEGF-A expression. We show that functional depletion of LSD1 expression using siRNA in prostate cancer cells decreases VEGF-A and blocks androgen induced VEGF-A, PSA and Tmprss2 expression. We demonstrate that pharmacological inhibition of LSD1 reduces proliferation of both androgen dependent (LnCaP) and independent cell lines (LnCaP: C42, PC3). We show a direct mechanistic link between LSD1 over-expression and increased activity of pro-angiogenic pathways. New therapies targeting LSD1 activity should be useful in the treatment of hormone dependent and independent prostate cancer.