METHODS: Forty healthy male SD rats were induced to diabetes with a single dose intra-peritoneal administration of STZ (60 mg/kg b.w.) - NAD (120 mg/kg b.w.). Diabetic rats were orally administered with 1 mL of pomegranate fresh juice (PJ) or 100 mg pomegranate seed powder in 1 mL distilled water (PS), or 5 mg/kg b.w. of glibenclamide every day for 21 days. Rats in all groups were sacrificed on day 22. The obtained data was analyzed by SPSS software (v: 22) using One-way analysis of variance (ANOVA).

RESULTS: The results showed that PJ and PS treatment had slight but non-significant reduction of plasma glucose concentration, and no impact on plasma insulin compared to diabetic control (DC) group. PJ lowered the plasma total cholesterol (TC) and triglyceride (TG) significantly, and low-density lipoproteins (LDL) non-significantly compared to DC group. In contrast, PS treatment significantly raised plasma TC, LDL, and high-density lipoproteins (HDL) levels compared to the DC rats. Moreover, the administration of PJ and PS significantly reduced the levels of plasma inflammatory biomarkers, which were actively raised in diabetic rats. Only PJ treated group showed significant repairment and restoration signs in islets of Langerhans. Besides, PJ possessed preventative impact against 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals almost 2.5 folds more than PS.

METHODS: This was a cross-sectional population based study with data on occupational social class, educational level obtained using a detailed health and lifestyle questionnaire. A total of 10,147 men and 12,304 women aged 45-80 years living in Norfolk, United Kingdom, were recruited using general practice age-sex registers as part of the European Prospective Investigation into Cancer (EPIC-Norfolk). Plasma levels of cholesterol and triglycerides were measured in baseline samples. Social class was classified according to three classifications: occupation, educational level, and area deprivation score according to Townsend deprivation index. Differences in lipid levels by socio-economic status indices were quantified by analysis of variance (ANOVA) and multiple linear regression after adjusting for body mass index and alcohol consumption.

RESULTS: Total cholesterol levels were associated with occupational level among men, and with educational level among women. Triglyceride levels were associated with educational level and occupational level among women, but the latter association was lost after adjustment for age and body mass index. HDL-cholesterol levels were associated with both educational level and educational level among men and women. The relationships with educational level were substantially attenuated by adjustment for age, body mass index and alcohol use, whereas the association with educational class was retained upon adjustment. LDL-cholesterol levels were not associated with social class indices among men, but a positive association was observed with educational class among women. This association was not affected by adjustment for age, body mass index and alcohol use.

DESIGN: Two cross-sectional studies using the WHO STEPS methodology.

SETTING: Both the urban and rural areas of the Yangon Region, Myanmar.

PARTICIPANTS: A total of 1370 men and women aged 25-74 years participated based on a multistage cluster sampling. Physically and mentally ill people, monks, nuns, soldiers and institutionalised people were excluded.

RESULTS: Compared with rural counterparts, urban dwellers had a significantly higher age-standardised prevalence of hypercholesterolaemia (50.7% vs 41.6%; p=0.042) and a low HDL level (60.6% vs 44.4%; p=0.001). No urban-rural differences were found in the prevalence of hypertriglyceridaemia and high LDL. Men had a higher age-standardised prevalence of hypertriglyceridaemia than women (25.1% vs 14.8%; p<0.001), while the opposite pattern was found in the prevalence of a high LDL (11.3% vs 16.3%; p=0.018) and low HDL level (35.3% vs 70.1%; p<0.001).Compared with rural inhabitants, urban dwellers had higher age-standardised mean levels of total cholesterol (5.31 mmol/L, SE: 0.044 vs 5.05 mmol/L, 0.068; p=0.009), triglyceride (1.65 mmol/L, 0.049 vs 1.38 mmol/L, 0.078; p=0.017), LDL (3.44 mmol/L, 0.019 vs 3.16 mmol/L, 0.058; p=0.001) and lower age-standardised mean levels of HDL (1.11 mmol/L, 0.010 vs 1.25 mmol/L, 0.012; p<0.001). In linear regression, the total cholesterol was significantly associated with an urban location among men, but not among women.

METHODS: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

RESULTS: Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.

CONCLUSIONS: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.