Adherence to predefined dietary patterns and incident type 2 diabetes in European populations: EPIC-InterAct Study

Aims/hypothesis - Few studies have investigated the relationship between predefined dietary patterns and type 2 diabetes incidence; little is known about the generalisability of these associations. We aimed to assess the association between predefined dietary patterns and type 2 diabetes risk in European populations. Methods - From among a case-cohort of 12,403 incident diabetes cases and 16,154 subcohort members nested within the prospective European Prospective Investigation into Cancer and Nutrition study, we used data on 9,682 cases and 12,595 subcohort participants from seven countries. Habitual dietary intake was assessed at baseline with country-specific dietary questionnaires. Two diet-quality scores (alternative Healthy Eating Index [aHEI], Dietary Approaches to Stop Hypertension [DASH] score) and three reduced rank regression (RRR)-derived dietary-pattern scores were constructed. Country-specific HRs were calculated and combined using a random-effects meta-analysis. Results - After multivariable adjustment, including body size, the aHEI and DASH scores were not significantly associated with diabetes, although for the aHEI there was a tendency towards an inverse association in countries with higher mean age. We observed inverse associations of the three RRR-derived dietary-pattern scores with diabetes: HRs (95% CIs) for a 1-SD difference were 0.91 (0.86, 0.96), 0.92 (0.84, 1.01) and 0.87 (0.82, 0.92). Random-effects meta-analyses revealed heterogeneity between countries that was explainable by differences in the age of participants or the distribution of dietary intake. Conclusions/interpretation - Adherence to specific RRR-derived dietary patterns, commonly characterised by high intake of fruits or vegetables and low intake of processed meat, sugar-sweetened beverages and refined grains, may lower type 2 diabetes risk

A misplaced lncRNA causes brachydactyly in humans

Translocations are chromosomal rearrangements that are frequently associated with a variety of disease states and developmental disorders. We identified 2 families with brachydactyly type E (BDE) resulting from different translocations affecting chromosome 12p. Both translocations caused downregulation of the parathyroid hormone-like hormone (PTHLH) gene by disrupting the cis-regulatory landscape. Using chromosome conformation capturing, we identified a regulator on chromosome 12q that interacts in cis with PTHLH over a 24.4-megabase distance and in trans with the sex-determining region Y-box 9 (SOX9) gene on chromosome 17q. The element also harbored a long noncoding RNA (lncRNA). Silencing of the lncRNA, PTHLH, or SOX9 revealed a feedback mechanism involving an expression-dependent network in humans. In the BDE patients, the human lncRNA was upregulated by the disrupted chromosomal association. Moreover, the lncRNA occupancy at the PTHLH locus was reduced. Our results document what we believe to be a novel in cis- and in trans-acting DNA and lncRNA regulatory feedback element that is reciprocally regulated by coding genes. Furthermore, our findings provide a systematic and combinatorial view of how enhancers encoding lncRNAs may affect gene expression in normal development

Circulating omentin as a novel biomarker for colorectal cancer risk: Data from the EPIC - Potsdam cohort study

Omentin is a novel biomarker shown to exert metabolic, inflammatory and immune-related properties, and thereby could be implicated in the risk of colorectal cancer (CRC). So far, the association between omentin and CRC risk has not been evaluated in prospective cohort studies. We investigated the association between pre-diagnostic plasma omentin concentrations and risk of CRC in a case-cohort comprising 251 incident CRC cases diagnosed over a mean follow-up time of 10.4 years and 2,295 persons who remained free of cancer in the European Prospective Investigation into Cancer and Nutrition-Potsdam study. Hazard ratios as a measure of relative risk (RR) and 95% confidence intervals (CI-s) were computed using a Prentice modified Cox regression. In a model adjusted for established CRC risk factors, age, sex, education, dietary and lifestyle factors, body mass index (BMI) and waist circumference, higher omentin concentrations were associated with a higher CRC risk (RRcontinuously per doubling of omentin concentrations=1.98, 95%CI: 1.45-2.73). Additional adjustment for metabolic biomarkers, including glycated hemoglobin, high-density lipoprotein cholesterol and C-reactive protein, did not alter the results. In stratified analyses, the positive association between omentin and CRC risk was retained in participants with BMI< 30 (RRcontinuously per doubling of omentin concentrations=2.26; 95%CI: 1.57-3.27), whereas among participants with BMI{greater than or equal to} 30 no association was revealed (RRcontinuously per doubling of omentin concentrations =1.07; 95%CI: 0.63-1.83; Pinteraction= 0.005). These novel findings provide the first lines of evidence for an independent association between pre-diagnostic omentin concentrations and CRC risk and suggest a potential interaction with the adiposity state of the individual

The Iterative Signature Algorithm for the analysis of large scale gene expression data

We present a new approach for the analysis of genome-wide expression data. Our method is designed to overcome the limitations of traditional techniques, when applied to large-scale data. Rather than alloting each gene to a single cluster, we assign both genes and conditions to context-dependent and potentially overlapping transcription modules. We provide a rigorous definition of a transcription module as the object to be retrieved from the expression data. An efficient algorithm, that searches for the modules encoded in the data by iteratively refining sets of genes and conditions until they match this definition, is established. Each iteration involves a linear map, induced by the normalized expression matrix, followed by the application of a threshold function. We argue that our method is in fact a generalization of Singular Value Decomposition, which corresponds to the special case where no threshold is applied. We show analytically that for noisy expression data our approach leads to better classification due to the implementation of the threshold. This result is confirmed by numerical analyses based on in-silico expression data. We discuss briefly results obtained by applying our algorithm to expression data from the yeast S. cerevisiae.Comment: Latex, 36 pages, 8 figure

Financial conflicts of interest and reporting bias regarding the association between sugar-sweetened beverages and weight gain: a systematic review of systematic reviews

Background: Industry sponsors’ financial interests might bias the conclusions of scientific research. We examined whether financial industry funding or the disclosure of potential conflicts of interest influenced the results of published systematic reviews (SRs) conducted in the field of sugar-sweetened beverages (SSBs) and weight gain or obesity. Methods and Findings: We conducted a search of the PubMed, Cochrane Library, and Scopus databases to identify published SRs from the inception of the databases to August 31, 2013, on the association between SSB consumption and weight gain or obesity. SR conclusions were independently classified by two researchers into two groups: those that found a positive association and those that did not. These two reviewers were blinded with respect to the stated source of funding and the disclosure of conflicts of interest. We identified 17 SRs (with 18 conclusions). In six of the SRs a financial conflict of interest with some food industry was disclosed. Among those reviews without any reported conflict of interest, 83.3% of the conclusions (10/12) were that SSB consumption could be a potential risk factor for weight gain. In contrast, the same percentage of conclusions, 83.3% (5/6), of those SRs disclosing some financial conflict of interest with the food industry were that the scientific evidence was insufficient to support a positive association between SSB consumption and weight gain or obesity. Those reviews with conflicts of interest were five times more likely to present a conclusion of no positive association than those without them (relative risk: 5.0, 95% CI: 1.3–19.3). An important limitation of this study is the impossibility of ruling out the existence of publication bias among those studies not declaring any conflict of interest. However, the best large randomized trials also support a direct association between SSB consumption and weight gain or obesity. Conclusions: Financial conflicts of interest may bias conclusions from SRs on SSB consumption and weight gain or obesity

Association of the human gut microbiota with vascular stiffness

Gut microbiota metabolites have been mechanistically linked to inflammatory pathway activation and atherosclerosis, which are major causes of vascular stiffness (VS). Aiming to investigate if the gut microbiome might be involved in VS development, we performed a cross-sectional study (n = 3,087), nested within the population-based European Prospective Investigations into Cancer and Nutrition (EPIC) Potsdam. We investigated the correlation of the gut microbiota (alpha diversity and taxa abundance) with 3 vascular stiffness measures: carotid-femoral (PWV), aortic augmentation index (AIX) and ankle-brachial index (ABI). Shannon index was not significantly associated with VS but the number of observed Amplicon Sequence Variants (ASV) was positively associated with PWV and AIX. We found a total of 19 ASVs significantly associated with at least one VS measure in multivariable-adjusted models. One ASV (classified as Sutterella wadsworthensis) was associated with 2 VS measures, AIX (- 0.11 ± 0.04) and PWV (-0.14 ± 0.03). Other examples of ASVs associated with VS were Collinsella aerofaciens, previously reported to be affected by diet and Bacteroides uniformis, commercially available as probiotics. In conclusion, our study suggests a potential role of individual components of the gut microbiota in the aetiology of VS

Prospective analysis of circulating metabolites and endometrial cancer risk

Background: Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods: A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed. Results: After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results. Conclusion: These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention

General and abdominal adiposity and risk of death in Europe

BACKGROUND Previous studies have relied predominantly on the body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) to assess the association of adiposity with the risk of death, but few have examined whether the distribution of body fat contributes to the prediction of death. METHODS We examined the association of BMI, waist circumference, and waist-to-hip ratio with the risk of death among 359,387 participants from nine countries in the European Prospective Investigation into Cancer and Nutrition (EPIC). We used a Cox regression analysis, with age as the time variable, and stratified the models according to study center and age at recruitment, with further adjustment for educational level, smoking status, alcohol consumption, physical activity, and height. RESULTS During a mean follow-up of 9.7 years, 14,723 participants died. The lowest risks of death related to BMI were observed at a BMI of 25.3 for men and 24.3 for women. After adjustment for BMI, waist circumference and waist-to-hip ratio were strongly associated with the risk of death. Relative risks among men and women in the highest quintile of waist circumference were 2.05 (95% confidence interval [CI], 1.80 to 2.33) and 1.78 (95% CI, 1.56 to 2.04), respectively, and in the highest quintile of waist-to-hip ratio, the relative risks were 1.68 (95% CI, 1.53 to 1.84) and 1.51 (95% CI, 1.37 to 1.66), respectively. BMI remained significantly associated with the risk of death in models that included waist circumference or waist-to-hip ratio (P<0.001). CONCLUSIONS These data suggest that both general adiposity and abdominal adiposity are associated with the risk of death and support the use of waist circumference or waist-tohip ratio in addition to BMI in assessing the risk of death