Prediction of Circulating Adipokine Levels Based on Body Fat Compartments and Adipose Tissue Gene Expression.

BACKGROUND: Adipokines are hormones secreted from adipose tissue (AT), and a number of them have been established as risk factors for chronic diseases. However, it is not clear whether and to what extent adiposity, gene expression, and other factors determine their circulating levels. OBJECTIVES: To assess to what extent adiposity, as measured by the amount of subcutaneous AT (SAT) and visceral AT (VAT) using magnetic resonance imaging, and gene expression levels in SAT determine plasma concentrations of the adipokines adiponectin, leptin, soluble leptin receptor, resistin, interleukin 6, and fatty acid-binding protein 4 (FABP4). METHODS: We performed a cross-sectional analysis of 156 participants from the EPIC Potsdam cohort study and analyzed multiple regression models and partial correlation coefficients. RESULTS: For leptin and FABP4 concentrations, 81 and 45% variance were explained by SAT mass, VAT mass, and gene expression in SAT in multivariable regression models. For the remaining adipokines, AT mass and gene expression explained <16% variance of plasma concentrations. Gene expression in SAT was a less important predictor compared to AT mass. SAT mass was a better predictor than VAT mass for leptin (partial correlation r = 0.81, 95% confidence interval 0.75-0.86, vs. r = 0.58, 95% confidence interval 0.46-0.67), while differences between AT compartments were small for the other adipokines. CONCLUSIONS: While plasma levels of leptin and FABP4 can be explained in a large and medium part by the amount of AT and SAT gene expression, surprisingly, these predictors explained only little variance for all other investigated adipokines.

Fatty Acid-Binding Protein 4 and Risk of Type 2 Diabetes, Myocardial Infarction, and Stroke: A Prospective Cohort Study.

CONTEXT: Adipocyte fatty acid-binding protein (FABP4) is expressed in adipose tissue and may impair glucose homeostasis and promote atherosclerotic processes. OBJECTIVE: We examined the association between serum FABP4 and risk of type 2 diabetes (T2D), myocardial infarction (MI), and stroke. DESIGN: Case-cohort study embedded within a sample of 27,548 participants of the EPIC-Potsdam cohort. PARTICIPANTS AND SETTING: A randomly selected subcohort (n = 2194) of participants who were free of cardiovascular disease and T2D at study baseline and 728 incident T2D cases, 206 incident stroke cases, and 185 incident MI cases with an average 8.2 (±1.7) years of follow-up. MAIN OUTCOME MEASURES: Incident T2D, MI, and stroke. RESULTS: In a multivariable-adjusted model, the hazard ratios (HRs) in the highest vs lowest quartile of FABP4 were 1.81 (95% CI, 1.21 to 2.70; Ptrend = 0.01) for T2D, 0.93 (95% CI, 0.55 to 1.55; Ptrend = 0.68) for MI, and 1.41 (95% CI, 0.80 to 2.49; Ptrend = 0.24) for stroke, respectively. In analyses stratified by sex, no statistically significant differences could be seen for associations between FABP4 and T2D and MI (Pinteraction by sex = 0.27 and 0.84, respectively), whereas a higher risk of stroke was observed in men (HR: 2.70, 95% CI 1.20 to 6.00; P = 0.04), but not in women (HR: 0.70, 95% CI 0.31 to 1.60; P = 0.53; Pinteraction = 0.02). CONCLUSIONS: These data support the hypothesis that elevated FABP4 levels may contribute to T2D risk. In contrast, our data did not support the hypothesis that circulating FABP4 may be relevant for MI, whereas the observed association with stroke in men may need further evaluation.

Physical activity, mediating factors and risk of colon cancer: insights into adiposity and circulating biomarkers from the EPIC cohort.

Background: There is convincing evidence that high physical activity lowers the risk of colon cancer; however, the underlying biological mechanisms remain largely unknown. We aimed to determine the extent to which body fatness and biomarkers of various biologically plausible pathways account for the association between physical activity and colon cancer. Methods: We conducted a nested case-control study in a cohort of 519 978 men and women aged 25 to 70 years followed from 1992 to 2003. A total of 713 incident colon cancer cases were matched, using risk-set sampling, to 713 controls on age, sex, study centre, fasting status and hormonal therapy use. The amount of total physical activity during the past year was expressed in metabolic equivalent of task [MET]-h/week. Anthropometric measurements and blood samples were collected at study baseline. Results: High physical activity was associated with a lower risk of colon cancer: relative risk ≥91 MET-h/week vs <91 MET-h/week = 0.75 [95% confidence interval (CI): 0.57 to 0.96]. In mediation analyses, this association was accounted for by waist circumference: proportion explained effect (PEE) = 17%; CI: 4% to 52%; and the biomarkers soluble leptin receptor (sOB-R): PEE = 15%; 95% CI: 1% to 50% and 5-hydroxyvitamin D (25[OH]D): PEE = 30%; 95% CI: 12% to 88%. In combination, these factors explained 45% (95% CI: 20% to 125%) of the association. Beyond waist circumference, sOB-R and 25[OH]D additionally explained 10% (95% CI: 1%; 56%) and 23% (95% CI: 6%; 111%) of the association, respectively. Conclusions: Promoting physical activity, particularly outdoors, and maintaining metabolic health and adequate vitamin D levels could represent a promising strategy for colon cancer prevention.

Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis.

BACKGROUND: The application of metabolomics in prospective cohort studies is statistically challenging. Given the importance of appropriate statistical methods for selection of disease-associated metabolites in highly correlated complex data, we combined random survival forest (RSF) with an automated backward elimination procedure that addresses such issues. METHODS: Our RSF approach was illustrated with data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study, with concentrations of 127 serum metabolites as exposure variables and time to development of type 2 diabetes mellitus (T2D) as outcome variable. Out of this data set, Cox regression with a stepwise selection method was recently published. Replication of methodical comparison (RSF and Cox regression) was conducted in two independent cohorts. Finally, the R-code for implementing the metabolite selection procedure into the RSF-syntax is provided. RESULTS: The application of the RSF approach in EPIC-Potsdam resulted in the identification of 16 incident T2D-associated metabolites which slightly improved prediction of T2D when used in addition to traditional T2D risk factors and also when used together with classical biomarkers. The identified metabolites partly agreed with previous findings using Cox regression, though RSF selected a higher number of highly correlated metabolites. CONCLUSIONS: The RSF method appeared to be a promising approach for identification of disease-associated variables in complex data with time to event as outcome. The demonstrated RSF approach provides comparable findings as the generally used Cox regression, but also addresses the problem of multicollinearity and is suitable for high-dimensional data.

Identification of Serum Metabolites Associated With Incident Hypertension in the European Prospective Investigation into Cancer and Nutrition-Potsdam Study.

Metabolomics is a promising tool to gain new insights into early metabolic alterations preceding the development of hypertension in humans. We therefore aimed to identify metabolites associated with incident hypertension using measured data of serum metabolites of the European Prospective Investigation Into Cancer and Nutrition (EPIC)-Potsdam study. Targeted metabolic profiling was conducted on serum blood samples of a randomly drawn EPIC-Potsdam subcohort consisting of 135 cases and 981 noncases of incident hypertension, all of them being free of hypertension and not on antihypertensive therapy at the time of blood sampling. Mean follow-up was 9.9 years. A validated set of 127 metabolites was statistically analyzed with a random survival forest backward selection algorithm to identify predictive metabolites of incident hypertension taking into account important epidemiological hypertension risk markers. Six metabolites were identified to be most predictive for the development of hypertension. Higher concentrations of serine, glycine, and acyl-alkyl-phosphatidylcholines C42:4 and C44:3 tended to be associated with higher and diacyl-phosphatidylcholines C38:4 and C38:3 with lower predicted 10-year hypertension-free survival, although visualization by partial plots revealed some nonlinearity in the above associations. The identified metabolites improved prediction of incident hypertension when used together with known risk markers of hypertension. In conclusion, these findings indicate that metabolic alterations occur early in the development of hypertension. However, these alterations are confined to a few members of the amino acid or phosphatidylcholine metabolism, respectively.

Combined effects of smoking and HPV16 in oropharyngeal cancer.

BACKGROUND: Although smoking and HPV infection are recognized as important risk factors for oropharyngeal cancer, how their joint exposure impacts on oropharyngeal cancer risk is unclear. Specifically, whether smoking confers any additional risk to HPV-positive oropharyngeal cancer is not understood. METHODS: Using HPV serology as a marker of HPV-related cancer, we examined the interaction between smoking and HPV16 in 459 oropharyngeal (and 1445 oral cavity and laryngeal) cancer patients and 3024 control participants from two large European multi-centre studies. Odds ratios and credible intervals [CrI], adjusted for potential confounders, were estimated using Bayesian logistic regression. RESULTS: Both smoking [odds ratio (OR [CrI]: 6.82 [4.52, 10.29]) and HPV seropositivity (OR [CrI]: 235.69 [99.95, 555.74]) were independently associated with oropharyngeal cancer. The joint association of smoking and HPV seropositivity was consistent with that expected on the additive scale (synergy index [CrI]: 1.32 [0.51, 3.45]), suggesting they act as independent risk factors for oropharyngeal cancer. CONCLUSIONS: Smoking was consistently associated with increase in oropharyngeal cancer risk in models stratified by HPV16 seropositivity. In addition, we report that the prevalence of oropharyngeal cancer increases with smoking for both HPV16-positive and HPV16-negative persons. The impact of smoking on HPV16-positive oropharyngeal cancer highlights the continued need for smoking cessation programmes for primary prevention of head and neck cancer.

Cellular immune activity biomarker neopterin is associated hyperlipidemia: results from a large population-based study.

BACKGROUND: Increased serum neopterin had been described in older age two decades ago. Neopterin is a biomarker of systemic adaptive immune activation that could be potentially implicated in metabolic syndrome (MetS). Measurements of waist circumference, triglycerides, high-density lipoprotein cholesterol (HDLC), systolic and diastolic blood pressure, glycated hemoglobin as components of MetS definition, and plasma total neopterin concentrations were performed in 594 participants recruited in the European Prospective Investigation into Cancer and Nutrition (EPIC). RESULTS: Higher total neopterin concentrations were associated with reduced HDLC (9.7 %, p < 0.01 for men and 9.2 %, p < 0.01 for women), whereas no association was observed with the rest of the MetS components as well as with MetS overall (per 10 nmol/L: OR = 1.42, 95 % CI = 0.85-2.39 for men and OR = 1.38, 95 % CI = 0.79-2.43). CONCLUSIONS: These data suggest that high total neopterin concentrations are cross-sectionally associated with reduced HDLC, but not with overall MetS.

Insulin-Like Growth Factor 1 and Insulin-Like Growth Factor-Binding Protein 3 in Relation to the Risk of Type 2 Diabetes Mellitus: Results From the EPIC-Potsdam Study.

Higher levels of insulin-like growth factor-binding protein 3 (IGFBP-3) might raise the risk of type 2 diabetes mellitus (T2DM) via binding of insulin-like growth factor 1 (IGF-1), an insulin-like hormone that is involved in glucose homeostasis. We investigated serum concentrations of IGF-1 and IGFBP-3 and their molar ratio in relation to T2DM incidence in a nested case-cohort study within the European Prospective Investigation Into Cancer and Nutrition-Potsdam Study. We included a randomly selected subcohort of persons without T2DM at the time of blood sampling (n = 2,269) and 776 individuals with incident T2DM identified between 1994 and 2005. For the highest quartile versus lowest, the multivariable-adjusted hazard rate ratios were 0.91 (95% confidence interval (CI): 0.68, 1.23; P for trend = 0.31) for IGF-1, 1.33 (95% CI: 1.00, 1.76; P for trend = 0.04) for IGFBP-3, and 0.77 (95% CI: 0.57, 1.03; P for trend = 0.03) for IGF-1:IGFBP-3 ratio. IGFBP-3 level remained positively associated with T2DM incidence-and the ratio of IGF-1 to IGFBP-3 was inversely related with T2DM incidence--in models that included adjustment for IGF-1 concentrations (P for trend < 0.05). Therefore, our findings do not confirm an association between total IGF-1 concentrations and risk of T2DM in the general study population, although higher IGFBP-3 levels might raise T2DM risk independent of IGF-1 levels.

The association of coffee intake with liver cancer risk is mediated by biomarkers of inflammation and hepatocellular injury: data from the European Prospective Investigation into Cancer and Nutrition.

BACKGROUND: Higher coffee intake has been purportedly related to a lower risk of liver cancer. However, it remains unclear whether this association may be accounted for by specific biological mechanisms. OBJECTIVE: We aimed to evaluate the potential mediating roles of inflammatory, metabolic, liver injury, and iron metabolism biomarkers on the association between coffee intake and the primary form of liver cancer-hepatocellular carcinoma (HCC). DESIGN: We conducted a prospective nested case-control study within the European Prospective Investigation into Cancer and Nutrition among 125 incident HCC cases matched to 250 controls using an incidence-density sampling procedure. The association of coffee intake with HCC risk was evaluated by using multivariable-adjusted conditional logistic regression that accounted for smoking, alcohol consumption, hepatitis infection, and other established liver cancer risk factors. The mediating effects of 21 biomarkers were evaluated on the basis of percentage changes and associated 95% CIs in the estimated regression coefficients of models with and without adjustment for biomarkers individually and in combination. RESULTS: The multivariable-adjusted RR of having ≥4 cups (600 mL) coffee/d compared with <2 cups (300 mL)/d was 0.25 (95% CI: 0.11, 0.62; P-trend = 0.006). A statistically significant attenuation of the association between coffee intake and HCC risk and thereby suspected mediation was confirmed for the inflammatory biomarker IL-6 and for the biomarkers of hepatocellular injury glutamate dehydrogenase, alanine aminotransferase, aspartate aminotransferase (AST), γ-glutamyltransferase (GGT), and total bilirubin, which-in combination-attenuated the regression coefficients by 72% (95% CI: 7%, 239%). Of the investigated biomarkers, IL-6, AST, and GGT produced the highest change in the regression coefficients: 40%, 56%, and 60%, respectively. CONCLUSION: These data suggest that the inverse association of coffee intake with HCC risk was partly accounted for by biomarkers of inflammation and hepatocellular injury.

Untargeted metabolic profiling identifies altered serum metabolites of type 2 diabetes mellitus in a prospective, nested case control study.

BACKGROUND: Application of metabolite profiling could expand the etiological knowledge of type 2 diabetes mellitus (T2D). However, few prospective studies apply broad untargeted metabolite profiling to reveal the comprehensive metabolic alterations preceding the onset of T2D. METHODS: We applied untargeted metabolite profiling in serum samples obtained from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort comprising 300 individuals who developed T2D after a median follow-up time of 6 years and 300 matched controls. For that purpose, we used ultraperformance LC-MS with a protocol specifically designed for large-scale metabolomics studies with regard to robustness and repeatability. After multivariate classification to select metabolites with the strongest contribution to disease classification, we applied multivariable-adjusted conditional logistic regression to assess the association of these metabolites with T2D. RESULTS: Among several alterations in lipid metabolism, there was an inverse association with T2D for metabolites chemically annotated as lysophosphatidylcholine(dm16:0) and phosphatidylcholine(O-20:0/O-20:0). Hexose sugars were positively associated with T2D, whereas higher concentrations of a sugar alcohol and a deoxyhexose sugar reduced the odds of diabetes by approximately 60% and 70%, respectively. Furthermore, there was suggestive evidence for a positive association of the circulating purine nucleotide isopentenyladenosine-5'-monophosphate with incident T2D. CONCLUSIONS: This study constitutes one of the largest metabolite profiling approaches of T2D biomarkers in a prospective study population. The findings might help generate new hypotheses about diabetes etiology and develop further targeted studies of a smaller number of potentially important metabolites.

Evaluation of various biomarkers as potential mediators of the association between coffee consumption and incident type 2 diabetes in the EPIC-Potsdam Study.

BACKGROUND: The inverse association between coffee consumption and the risk of type 2 diabetes (T2D) is well established; however, little is known about potential mediators of this association. OBJECTIVE: We aimed to investigate the association between coffee consumption and diabetes-related biomarkers and their potential role as mediators of the association between coffee consumption and T2D. DESIGN: We analyzed a case-cohort study (subcohort: n = 1610; verified incident T2D cases: n = 417) nested within the European Prospective Investigation into Cancer and Nutrition-Potsdam study involving 27,548 middle-aged participants. Habitual coffee consumption was assessed with a validated, semiquantitative food-frequency questionnaire. We evaluated the association between coffee consumption and several T2D-related biomarkers, such as liver markers (reflected by γ-glutamyltransferase, fetuin-A, and sex hormone-binding globulin), markers of dyslipidemia (high-density lipoprotein cholesterol and triglycerides), inflammation [C-reactive protein (CRP)], an adipokine (adiponectin), and metabolites, stratified by sex. RESULTS: Coffee consumption was inversely associated with diacyl-phosphatidylcholine C32:1 in both sexes and with phenylalanine in men, as well as positively associated with acyl-alkyl-phosphatidylcholines C34:3, C40:6, and C42:5 in women. Furthermore, coffee consumption was inversely associated with fetuin-A (P-trend = 0.06) and CRP in women and γ-glutamyltransferase and triglycerides in men. Coffee consumption tended to be inversely associated with T2D risk in both sexes, reaching significance only in men [HR (95% CI): women: ≥4 compared with >0 to <2 cups coffee/d: 0.78 (0.46, 1.33); men: ≥5 compared with >0 to <2 cups coffee/d: 0.40 (0.19, 0.81)]. The association between coffee consumption and T2D risk in men was slightly reduced after adjustment for phenylalanine or lipid markers. CONCLUSIONS: Coffee consumption was inversely associated with a diacyl-phosphatidylcholine and liver markers in both sexes and positively associated with certain acyl-alkyl-phosphatidylcholines in women. Furthermore, coffee consumption showed an inverse trend with CRP in women and with triglycerides and phenylalanine in men. However, these markers explained only to a small extent the inverse association between long-term coffee consumption and T2D risk.

Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data.

OBJECTIVE: To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease. DESIGN: Mendelian randomisation meta-analysis of 56 epidemiological studies. PARTICIPANTS: 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers. MAIN OUTCOME MEASURES: Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption. RESULTS: Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)). CONCLUSIONS: Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health.

t(14;18) Translocation: A predictive blood biomarker for follicular lymphoma.

PURPOSE: The (14;18) translocation constitutes both a genetic hallmark and critical early event in the natural history of follicular lymphoma (FL). However, t(14;18) is also detectable in the blood of otherwise healthy persons, and its relationship with progression to disease remains unclear. Here we sought to determine whether t(14;18)-positive cells in healthy individuals represent tumor precursors and whether their detection could be used as an early predictor for FL. PARTICIPANTS AND METHODS: Among 520,000 healthy participants enrolled onto the EPIC (European Prospective Investigation Into Cancer and Nutrition) cohort, we identified 100 who developed FL 2 to 161 months after enrollment. Prediagnostic blood from these and 218 controls were screened for t(14;18) using sensitive polymerase chain reaction-based assays. Results were subsequently validated in an independent cohort (65 case participants; 128 controls). Clonal relationships between t(14;18) cells and FL were also assessed by molecular backtracking of paired prediagnostic blood and tumor samples. RESULTS: Clonal analysis of t(14;18) junctions in paired prediagnostic blood versus tumor samples demonstrated that progression to FL occurred from t(14;18)-positive committed precursors. Furthermore, healthy participants at enrollment who developed FL up to 15 years later showed a markedly higher t(14;18) prevalence and frequency than controls (P < .001). Altogether, we estimated a 23-fold higher risk of subsequent FL in blood samples associated with a frequency > 10(-4) (odds ratio, 23.17; 95% CI, 9.98 to 67.31; P < .001). Remarkably, risk estimates remained high and significant up to 15 years before diagnosis. CONCLUSION: High t(14;18) frequency in blood from healthy individuals defines the first predictive biomarker for FL, effective years before diagnosis.

Serum metabolites related to cardiorespiratory fitness, physical activity energy expenditure, sedentary time and vigorous activity.

The aim of our study was to investigate the relationship between objectively measured physical activity (PA) and cardiorespiratory fitness (CRF) and serum metabolites measured by targeted metabolomics in a population- based study. A total of 100 subjects provided 2 fasting blood samples and engaged in a CRF and PA measurement at 2 visits 4 months apart. CRF was estimated from a step test, whereas physical activity energy expenditure (PAEE), time spent sedentary and time spend in vigorous activity were measured by a combined heart rate and movement sensor for a total of 8 days. Serum metabolite concentrations were determined by flow injection analysis tandem mass spectrometry (FIA-MS/MS). Linear mixed models were applied with multivariable adjustment and p-values were corrected for multiple testing. Furthermore, we explored the associations between CRF, PA and two metabolite factors that have previously been linked to risk of Type 2 diabetes. CRF was associated with two phosphatidylcholine clusters independently of all other exposures. Lysophosphatidylcholine C14:0 and methionine were significantly negatively associated with PAEE and sedentary time. CRF was positively associated with the Type 2 diabetes protective factor. Vigorous activity was positively associated with the Type 2 diabetes risk factor in the mutually adjusted model. Our results suggest that CRF and PA are associated with serum metabolites, especially CRF with phosphatidylcholines and with the Type 2 diabetes protective factor. PAEE and sedentary time were associated with methionine. The identified metabolites could be potential mediators of the protective effects of CRF and PA on chronic disease risk.

Adiposity, mediating biomarkers and risk of colon cancer in the European prospective investigation into cancer and nutrition study.

Adiposity is a risk factor for colon cancer, but underlying mechanisms are not well understood. We evaluated the extent to which 11 biomarkers with inflammatory and metabolic actions mediate the association of adiposity measures, waist circumference (WC) and body mass index (BMI), with colon cancer in men and women. We analyzed data from a prospective nested case-control study among 662 incident colon cancer cases matched within risk sets to 662 controls. Relative risks (RRs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression. The percent effect change and corresponding CIs were estimated after adjusting for biomarkers shown to be associated with colon cancer risk. After multivariable adjustment, WC was associated with colon cancer risk in men (top vs. bottom tertile RR 1.68, 95% CI 1.06-2.65; ptrend = 0.02) and in women (RR 1.67, 95% CI 1.09-2.56; ptrend = 0.03). BMI was associated with risk only in men. The association of WC with colon cancer was accounted mostly for by three biomarkers, high-density lipoprotein cholesterol, non-high-molecular-weight adiponectin and soluble leptin receptor, which in combination explained 46% (95% CI 37-57%) of the association in men and 50% (95% CI 40-65%) of the association in women. Similar results were observed for the associations with BMI in men. These data suggest that alterations in levels of these metabolic biomarkers may represent a primary mechanism of action in the relation of adiposity with colon cancer. Further studies are warranted to determine whether altering their concentrations may reduce colon cancer risk.

Methylome analysis and epigenetic changes associated with menarcheal age.

Reproductive factors have been linked to both breast cancer and DNA methylation, suggesting methylation as an important mechanism by which reproductive factors impact on disease risk. However, few studies have investigated the link between reproductive factors and DNA methylation in humans. Genome-wide methylation in peripheral blood lymphocytes of 376 healthy women from the prospective EPIC study was investigated using LUminometric Methylation Assay (LUMA). Also, methylation of 458877 CpG sites was additionally investigated in an independent group of 332 participants of the EPIC-Italy sub-cohort, using the Infinium HumanMethylation 450 BeadChip. Multivariate logistic regression and linear models were used to investigate the association between reproductive risk factors and genome wide and CpG-specific DNA methylation, respectively. Menarcheal age was inversely associated with global DNA methylation as measured with LUMA. For each yearly increase in age at menarche, the risk of having genome wide methylation below median level was increased by 32% (OR:1.32, 95%CI:1.14-1.53). When age at menarche was treated as a categorical variable, there was an inverse dose-response relationship with LUMA methylation levels (OR(12-14 vs. ≤11 yrs):1.78, 95%CI:1.01-3.17 and OR(≥15 vs. ≤11 yrs):4.59, 95%CI:2.04-10.33; P for trend<0.0001). However, average levels of global methylation as measured by the Illumina technology were not significantly associated with menarcheal age. In locus by locus comparative analyses, only one CpG site had significantly different methylation depending on the menarcheal age category examined, but this finding was not replicated by pyrosequencing in an independent data set. This study suggests a link between age at menarche and genome wide DNA methylation, and the difference in results between the two arrays suggests that repetitive element methylation has a role in the association. Epigenetic changes may be modulated by menarcheal age, or the association may be a mirror of other important changes in early life that have a detectable effect on both methylation levels and menarcheal age.

Evaluation of 41 candidate gene variants for obesity in the EPIC-Potsdam cohort by multi-locus stepwise regression.

OBJECTIVE: Obesity has become a leading preventable cause of morbidity and mortality in many parts of the world. It is thought to originate from multiple genetic and environmental determinants. The aim of the current study was to introduce haplotype-based multi-locus stepwise regression (MSR) as a method to investigate combinations of unlinked single nucleotide polymorphisms (SNPs) for obesity phenotypes. METHODS: In 2,122 healthy randomly selected men and women of the EPIC-Potsdam cohort, the association between 41 SNPs from 18 obesity-candidate genes and either body mass index (BMI, mean=25.9 kg/m(2), SD=4.1) or waist circumference (WC, mean=85.2 cm, SD=12.6) was assessed. Single SNP analyses were done by using linear regression adjusted for age, sex, and other covariates. Subsequently, MSR was applied to search for the 'best' SNP combinations. Combinations were selected according to specific AICc and p-value criteria. Model uncertainty was accounted for by a permutation test. RESULTS: The strongest single SNP effects on BMI were found for TBC1D1 rs637797 (ß = -0.33, SE=0.13), FTO rs9939609 (ß=0.28, SE=0.13), MC4R rs17700144 (ß=0.41, SE=0.15), and MC4R rs10871777 (ß=0.34, SE=0.14). All these SNPs showed similar effects on waist circumference. The two 'best' six-SNP combinations for BMI (global p-value= 3.45⋅10(-6) and 6.82⋅10(-6)) showed effects ranging from -1.70 (SE=0.34) to 0.74 kg/m(2) (SE=0.21) per allele combination. We selected two six-SNP combinations on waist circumference (global p-value = 7.80⋅10(-6) and 9.76⋅10(-6)) with an allele combination effect of -2.96 cm (SE=0.76) at maximum. Additional adjustment for BMI revealed 15 three-SNP combinations (global p-values ranged from 3.09⋅10(-4) to 1.02⋅10(-2)). However, after carrying out the permutation test all SNP combinations lost significance indicating that the statistical associations might have occurred by chance. CONCLUSION: MSR provides a tool to search for risk-related SNP combinations of common traits or diseases. However, the search process does not always find meaningful SNP combinations in a dataset.

Liver enzymes and stroke risk in middle-aged German adults.

OBJECTIVE: To investigate the association between the liver enzymes γ-glutamyltransferase (GGT) and (alanine aminotransferase) ALT and risk of stroke, its subtypes including TIA as well as fatal and non-fatal events. METHODS: A case-cohort study within the European Prospective Investigation into Cancer and Nutrition-Potsdam Study comprising 27548 middle-aged subjects was designed. GGT and ALT were measured in plasma of 353 individuals who developed a stroke and in 2110 individuals who remained free of cardiovascular events during a mean follow-up of 8.2 ± 2.2 years. Cox proportional-hazard models were applied to evaluate the association between liver enzymes and stroke risk. RESULTS: After adjustment for established clinical and lifestyle factors, a 1 unit change in naturally logged GGT was related to a 1.20 (95%CI: 1.03-1.40) increased stroke risk. Risk estimates did not significantly differ between fatal (Relative Risk (RR) = 1.35, 95%CI: 1.14-1.61) and non-fatal events (RR = 1.15; 95%CI: 0.97-1.36). ALT was not associated with overall stroke risk (RR = 0.95; 95%CI: 0.71-1.26). However, in subtype analyses we observed in multivariable adjusted models a significant increased risk of hemorrhagic stroke (RR = 2.00; 95% CI: 1.01-3.96), but decreased risk of ischemic stroke (RR = 0.66; 95%CI: 0.44-0.998). CONCLUSIONS: Our data provide further evidence for a link between GGT, but not ALT and overall stroke suggesting that these biomarkers are involved in different pathways of disease development. Further studies are needed to clarify the putative relationships between ALT and subtypes of stroke.

Hormonal, metabolic, and inflammatory profiles and endometrial cancer risk within the EPIC cohort--a factor analysis.

A "Western" lifestyle characterized by physical inactivity and excess weight is associated with a number of metabolic and hormonal dysregulations, including increased circulating estrogen levels, hyperinsulinemia, hyperglycemia, and chronic inflammation. The same hormonal and metabolic axes might mediate the association between this lifestyle and the development of endometrial cancer. Using data collected within the European Prospective Investigation into Cancer and Nutrition (EPIC), a prospective cohort study carried out in 10 European countries during 1992-2000, we conducted a factor analysis to delineate important components that summarize the variation explained by a set of biomarkers and to examine their association with endometrial cancer risk. Prediagnostic levels of testosterone, androstenedione, dehydroepiandrosterone sulfate, sex hormone-binding globulin, estrone, estradiol, C-peptide, insulin-like growth factor-binding proteins 1 and 2, adiponectin, high- and low-density lipoprotein cholesterol, glucose, triglycerides, tumor necrosis factor (TNF) α, soluble TNF receptors 1 and 2, C-reactive protein, interleukin-6, and interleukin-1 receptor antagonist were measured in 233 incident endometrial cancer cases and 446 matched controls. Factor analysis identified 3 components associated with postmenopausal endometrial cancer risk that could be labeled "insulin resistance/metabolic syndrome," "steroids," and "inflammation" factors. A fourth component, "lipids," was not significantly associated with endometrial cancer. In conclusion, besides the well-known associations of risk with sex hormones and insulin-regulated physiological axes, our data further support the hypothesis that inflammation factors play a role in endometrial carcinogenesis.

Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach.

Metabolomic discovery of biomarkers of type 2 diabetes (T2D) risk may reveal etiological pathways and help to identify individuals at risk for disease. We prospectively investigated the association between serum metabolites measured by targeted metabolomics and risk of T2D in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) among all incident cases of T2D (n = 800, mean follow-up 7 years) and a randomly drawn subcohort (n = 2,282). Flow injection analysis tandem mass spectrometry was used to quantify 163 metabolites, including acylcarnitines, amino acids, hexose, and phospholipids, in baseline serum samples. Serum hexose; phenylalanine; and diacyl-phosphatidylcholines C32:1, C36:1, C38:3, and C40:5 were independently associated with increased risk of T2D and serum glycine; sphingomyelin C16:1; acyl-alkyl-phosphatidylcholines C34:3, C40:6, C42:5, C44:4, and C44:5; and lysophosphatidylcholine C18:2 with decreased risk. Variance of the metabolites was largely explained by two metabolite factors with opposing risk associations (factor 1 relative risk in extreme quintiles 0.31 [95% CI 0.21-0.44], factor 2 3.82 [2.64-5.52]). The metabolites significantly improved T2D prediction compared with established risk factors. They were further linked to insulin sensitivity and secretion in the Tübingen Family study and were partly replicated in the independent KORA (Cooperative Health Research in the Region of Augsburg) cohort. The data indicate that metabolic alterations, including sugar metabolites, amino acids, and choline-containing phospholipids, are associated early on with a higher risk of T2D.