Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD ) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66-0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57-0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69-0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61-0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.
Polyphenols have been shown to exert biological activity in experimental models of colon cancer; however, human data linking specific polyphenols to colon cancer is limited. We assessed the relationship between pre-diagnostic plasma polyphenols and colon cancer risk in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition study. Using high pressure liquid chromatography coupled to tandem mass spectrometry, we measured concentrations of 35 polyphenols in plasma from 809 incident colon cancer cases and 809 matched controls. We used multivariable adjusted conditional logistic regression models that included established colon cancer risk factors. The false discovery rate (qvalues ) was computed to control for multiple comparisons. All statistical tests were two-sided. After false discovery rate correction and in continuous log2 -transformed multivariable models, equol (odds ratio [OR] per log2 -value, 0.86, 95% confidence interval [95% CI] = 0.79-0.93; qvalue = 0.01) and homovanillic acid (OR per log2 -value, 1.46, 95% CI = 1.16-1.84; qvalue = 0.02) were associated with colon cancer risk. Comparing extreme fifths, equol concentrations were inversely associated with colon cancer risk (OR = 0.61, 95% CI = 0.41-0.91, ptrend = 0.003), while homovanillic acid concentrations were positively associated with colon cancer development (OR = 1.72, 95% CI = 1.17-2.53, ptrend
Metabolomics is now widely used to characterize metabolic phenotypes associated with lifestyle risk factors such as obesity. The objective of the present study was to explore the associations of body mass index (BMI) with 145 metabolites measured in blood samples in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolites were measured in blood from 392 men from the Oxford (UK) cohort (EPIC-Oxford) and in 327 control subjects who were part of a nested case-control study on hepatobiliary carcinomas (EPIC-Hepatobiliary). Measured metabolites included amino acids, acylcarnitines, hexoses, biogenic amines, phosphatidylcholines, and sphingomyelins. Linear regression models controlled for potential confounders and multiple testing were run to evaluate the associations of metabolite concentrations with BMI. 40 and 45 individual metabolites showed significant differences according to BMI variations, in the EPIC-Oxford and EPIC-Hepatobiliary subcohorts, respectively. Twenty two individual metabolites (kynurenine, one sphingomyelin, glutamate and 19 phosphatidylcholines) were associated with BMI in both subcohorts. The present findings provide additional knowledge on blood metabolic signatures of BMI in European adults, which may help identify mechanisms mediating the relationship of BMI with obesity-related diseases.
Experimental studies have reported on the anti-inflammatory properties of polyphenols. However, results from epidemiological investigations have been inconsistent and especially studies using biomarkers for assessment of polyphenol intake have been scant. We aimed to characterise the association between plasma concentrations of thirty-five polyphenol compounds and low-grade systemic inflammation state as measured by high-sensitivity C-reactive protein (hsCRP). A cross-sectional data analysis was performed based on 315 participants in the European Prospective Investigation into Cancer and Nutrition cohort with available measurements of plasma polyphenols and hsCRP. In logistic regression analysis, the OR and 95 % CI of elevated serum hsCRP (>3 mg/l) were calculated within quartiles and per standard deviation higher level of plasma polyphenol concentrations. In a multivariable-adjusted model, the sum of plasma concentrations of all polyphenols measured (per standard deviation) was associated with 29 (95 % CI 50, 1) % lower odds of elevated hsCRP. In the class of flavonoids, daidzein was inversely associated with elevated hsCRP (OR 0·66, 95 % CI 0·46, 0·96). Among phenolic acids, statistically significant associations were observed for 3,5-dihydroxyphenylpropionic acid (OR 0·58, 95 % CI 0·39, 0·86), 3,4-dihydroxyphenylpropionic acid (OR 0·63, 95 % CI 0·46, 0·87), ferulic acid (OR 0·65, 95 % CI 0·44, 0·96) and caffeic acid (OR 0·69, 95 % CI 0·51, 0·93). The odds of elevated hsCRP were significantly reduced for hydroxytyrosol (OR 0·67, 95 % CI 0·48, 0·93). The present study showed that polyphenol biomarkers are associated with lower odds of elevated hsCRP. Whether diet rich in bioactive polyphenol compounds could be an effective strategy to prevent or modulate deleterious health effects of inflammation should be addressed by further well-powered longitudinal studies.
Perturbations in levels of amino acids (AA) and their derivatives are observed in hepatocellular carcinoma (HCC). Yet, it is unclear whether these alterations precede or are a consequence of the disease, nor whether they pertain to anatomically related cancers of the intrahepatic bile duct (IHBC), and gallbladder and extrahepatic biliary tract (GBTC). Circulating standard AA, biogenic amines and hexoses were measured (Biocrates AbsoluteIDQ-p180Kit) in a case-control study nested within a large prospective cohort (147 HCC, 43 IHBC and 134 GBTC cases). Liver function and hepatitis status biomarkers were determined separately. Multivariable conditional logistic regression was used to calculate odds ratios and 95% confidence intervals (OR; 95%CI) for log-transformed standardised (mean = 0, SD = 1) serum metabolite levels and relevant ratios in relation to HCC, IHBC or GBTC risk. Fourteen metabolites were significantly associated with HCC risk, of which seven metabolites and four ratios were the strongest predictors in continuous models. Leucine, lysine, glutamine and the ratio of branched chain to aromatic AA (Fischer's ratio) were inversely, while phenylalanine, tyrosine and their ratio, glutamate, glutamate/glutamine ratio, kynurenine and its ratio to tryptophan were positively associated with HCC risk. Confounding by hepatitis status and liver enzyme levels was observed. For the other cancers no significant associations were observed. In conclusion, imbalances of specific AA and biogenic amines may be involved in HCC development.
Identifying the metabolites associated with alcohol consumption may provide insights into the metabolic pathways through which alcohol may affect human health. We studied associations of alcohol consumption with circulating concentrations of 123 metabolites among 2974 healthy participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Alcohol consumption at recruitment was self-reported through dietary questionnaires. Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQTM p180 kit). Data were randomly divided into discovery (2/3) and replication (1/3) sets. Multivariable linear regression models were used to evaluate confounder-adjusted associations of alcohol consumption with metabolite concentrations. Metabolites significantly related to alcohol intake in the discovery set (FDR q-value < 0.05) were further tested in the replication set (Bonferroni-corrected p-value < 0.05). Of the 72 metabolites significantly related to alcohol intake in the discovery set, 34 were also significant in the replication analysis, including three acylcarnitines, the amino acid citrulline, four lysophosphatidylcholines, 13 diacylphosphatidylcholines, seven acyl-alkylphosphatidylcholines, and six sphingomyelins. Our results confirmed earlier findings that alcohol consumption was associated with several lipid metabolites, and possibly also with specific acylcarnitines and amino acids. This provides further leads for future research studies aiming at elucidating the mechanisms underlying the effects of alcohol in relation to morbid conditions.