PATIENTS AND METHODS: Fasting plasma PP concentrations were measured in 104 overweight and obese subjects (46 men and 58 women). In the same subjects, total and regional adipose tissue, including total visceral adipose tissue (VAT) and total subcutaneous adipose tissue (TSAT), were measured using whole-body magnetic resonance imaging. Intrahepatocellular lipid content (IHCL) was quantified by proton magnetic resonance spectroscopy.
RESULTS: Fasting plasma PP concentrations positively and significantly correlated with both VAT (r = 0.57, P < .001) and IHCL (r = 0.51, P < .001), but not with TSAT (r = 0.02, P = .88). Fasting PP concentrations independently predicted VAT after controlling for age and sex. Fasting PP concentrations independently predicted IHCL after controlling for age, sex, body mass index (BMI), waist-to-hip ratio, homeostatic model assessment 2-insulin resistance, (HOMA2-IR) and serum concentrations of triglyceride (TG), total cholesterol (TC), and alanine aminotransferase (ALT). Fasting PP concentrations were associated with serum ALT, TG, TC, low- and high-density lipoprotein cholesterol, and blood pressure (P < .05). These associations were mediated by IHCL and/or VAT. Fasting PP and HOMA2-IR were independently significantly associated with hepatic steatosis (P < .01).
CONCLUSIONS: Pancreatic polypeptide is a novel predictor of visceral and liver fat content, and thus a potential biomarker for cardiovascular risk stratification and targeted treatment of patients with ectopic fat deposition.
OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.
MATERIALS AND METHODS: A multicentre prospective cohort study was conducted among employees from 2 different public universities in Malaysia. Interventions include at least 2 sessions of behavioural therapy combined with free nicotine replacement therapy (NRT) for 8 weeks. Participants were followed up for 6 months. Independent variables assessed were on sociodemographic and environmental tobacco smoke. Their quit status were determined at 1 week, 3 months and 6 months.
RESULTS: One hundred and eighty- five smokers volunteered to participate. Among the participants, 15% and 13% sustained quit at 3 months and 6 months respectively. Multivariate analysis revealed that at 6 months, attending all 3 behavioural sessions predicted success. None of the environmental tobacco exposure variables were predictive of sustained cessation.
CONCLUSION: Individual predictors of success in intra-workplace smoking cessation programmes do not differ from the conventional clinic-based smoking cessation. Furthermore, environmental tobacco exposure in low intensity smoke-free workplaces has limited influence on smokers who succeeded in maintaining 6 months quitting.