Paolo Vineis

National Cancer Institute (USA), 베서스다, Maryland, United States

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Publications (596)3969.25 Total impact

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    ABSTRACT: Purpose: The strong association between t(14;18) translocation and follicular lymphoma (FL) is well known. However, the determinants of this chromosomal aberration and their role in t(14;18) associated FL remain to be established. Methods: t(14;18) frequency within the B cell lymphoma 2 major breakpoint region was determined for 135 incident FL cases and 251 healthy controls as part of a nested case-control study within the European Prospective Investigation into Cancer cohort. Quantitative real-time PCR was performed in DNA extracted from blood samples taken at recruitment. The relationship between prevalence and frequency of the translocation with baseline anthropometric, lifestyle, and dietary factors in cases and controls was determined. Unconditional logistic regression was used to explore whether the risk of FL associated with these factors differed in t(14;18)(+) as compared to t(14;18)(-) cases. Results: Among incident FL cases, educational level (χ (2) p = 0.021) and height (χ (2) p = 0.025) were positively associated with t(14;18) prevalence, and cases with high frequencies [t(14;18)(HF)] were significantly taller (t test p value = 0.006). These findings were not replicated in the control population, although there were a number of significant associations with dietary variables. Further analyses revealed that height was a significant risk factor for t(14;18)(+) FL [OR 6.31 (95 % CI 2.11, 18.9) in the tallest versus the shortest quartile], but not t(14;18)(-) cases. Conclusions: These findings suggest a potential role for lifestyle factors in the prevalence and frequency of the t(14;18) translocation. The observation that the etiology of FL may differ by t(14;18) status, particularly with regard to height, supports the subdivision of FL by translocation status.
    Cancer Causes and Control 10/2015; DOI:10.1007/s10552-015-0677-2 · 2.74 Impact Factor
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    ABSTRACT: Background Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers. Methods To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort. Results A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis. Conclusion Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer. Electronic supplementary material The online version of this article (doi:10.1186/s12916-015-0462-9) contains supplementary material, which is available to authorized users.
    BMC Medicine 09/2015; 13. DOI:10.1186/s12916-015-0462-9 · 7.25 Impact Factor
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    ABSTRACT: High blood pressure, which affects more than 1 billion people worldwide , is a major risk factor for myocardial infarction, stroke and chronic kidney disease. Approximately 9 million deaths each year are attributable to high blood pressure, including >50% of deaths from coronary heart disease and stroke 1,2. High blood pressure is more prevalent in people of East Asian and South Asian ancestry and is a major contributor to their increased risk of stroke and coronary heart disease 3,4. Genome-wide association studies (GWAS) have identified over 50 genetic loci influencing blood pressure in predominantly European populations 5–16. A role for epigenetic mechanisms in blood pressure regulation has also been suggested 17–20. We carried out a GWAS in East Asians and South Asians, as well as Europeans, to seek both cosmopolitan and population-specific genetic effects for five blood pressure phenotypes: systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure, mean arterial pressure (MAP) and hypertension (Supplementary Fig. 1) (ref. 5). We then sought DNA coding and gene regulatory mechanisms, including DNA methylation and gene transcription, to help explain the relationships we observed between sequence variation and blood pressure. RESULTS Genome-wide association and replication testing We used genome-wide association data from 99,994 individuals of East Asian (n = 31,516), European (n = 35,352) and South Asian (n = 33,126) ancestry. Characteristics of the participants and information on the genotyping arrays and imputation are summarized in Supplementary Tables 1–3. Phenotype-specific meta-analysis was carried out separately for East Asian, European and South Asian samples, followed by a meta-analysis across the three ancestral population groups. The trans-ancestry genome-wide association results identified 4,077 variants with P < 1 × 10 −4 against any blood pressure phenotype, distributed among 630 genetic loci. At each locus, we identified the sentinel SNP (the SNP with the lowest P value against any phenotype) and carried out combined analysis with phenotype-specific results from the International Consortium on Blood Pressure (ICBP) GWAS (maximum n = 87,205) (refs. 8,9). This analysis identified 19 previously unreported loci where the sentinel SNP had suggestive evidence for association with blood pressure (P < 1 × 10 −7
    Nature Genetics 09/2015; DOI:10.1038/ng.3405 · 29.35 Impact Factor
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    ABSTRACT: The five-target '25 × 25' strategy for tackling the emerging global epidemic of non-communicable diseases (NCDs) focuses on four diseases (CVD, diabetes, cancer, and chronic respiratory disease), four risk factors (tobacco, diet and physical activity, dietary salt, and alcohol), and one cardiovascular preventive drug treatment. The goal is to decrease mortality from NCDs by 25 per cent by the year 2025. The 'standard approach' to the '25 × 25' strategy has the benefit of simplicity, but also has major weaknesses. These include lack of recognition of: (i) the fundamental drivers of the NCD epidemic; (ii) the 'missing NCDs', which are major causes of morbidity; (iii) the 'missing causes' and the 'causes of the causes'; and (iv) the role of health care and the need for integration of interventions.Journal of Public Health Policy advance online publication, 17 September 2015; doi:10.1057/jphp.2015.29.
    Journal of Public Health Policy 09/2015; DOI:10.1057/jphp.2015.29 · 1.78 Impact Factor
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    ABSTRACT: Background/aims: Large epidemiological prospective studies represent an important opportunity for investigating risk factors for rare diseases such as Parkinson's disease (PD). Here we describe the procedures we used for ascertaining PD cases in the EPIC (European Prospective Investigation into Cancer and Nutrition) study. Methods: The following three-phase procedure was used: (1) elaboration of a NeuroEPIC4PD template for clinical data collection, (2) identification of all potential PD cases via record linkage and (3) validation of the diagnosis through clinical record revision, in a population of 220,494 subjects recruited in 7 European countries. All cases were labelled with the NeuroEPIC4PD diagnoses of 'definite', 'very likely', 'probable', or 'possible' PD. Results: A total of 881 PD cases were identified, with over 2,741,780 person-years of follow-up (199 definite, 275 very likely, 146 probable, and 261 possible). Of these, 734 were incident cases. The mean age at diagnosis was 67.9 years (SD 9.2) and 458 patients (52.0%) were men. Bradykinesia was the most frequent presenting motor sign (76.5%). Tremor-dominant and akinetic rigid forms of PD were the most common types of PD. A total of 289 patients (32.8%) were dead at the time of the last follow-up. Conclusions: This exercise proved that it is feasible to ascertain PD in large population-based cohort studies and offers a potential framework to be replicated in similar studies.
    Neurodegenerative Diseases 09/2015; DOI:10.1159/000381857 · 3.51 Impact Factor
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    ABSTRACT: Objective Although metabolic profiles have been associated with chronic disease risk, lack of temporal stability of metabolite levels could limit their use in epidemiological investigations. The present study aims to evaluate the reliability over a two-year period of 158 metabolites and compare reliability over time in fasting and non-fasting serum samples. Methods Metabolites were measured with the AbsolueIDQp180 kit (Biocrates, Innsbruck, Austria) by mass spectrometry and included acylcarnitines, amino acids, biogenic amines, hexoses, phosphatidylcholines and sphingomyelins. Measurements were performed on repeat serum samples collected two years apart in 27 fasting men from Turin, Italy, and 39 non-fasting women from Utrecht, The Netherlands, all participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Reproducibility was assessed by estimating intraclass correlation coefficients (ICCs) in multivariable mixed models. Results In fasting samples, a median ICC of 0.70 was observed. ICC values were <0.50 for 48% of amino acids, 27% of acylcarnitines, 18% of lysophosphatidylcholines and 4% of phosphatidylcholines. In non-fasting samples, the median ICC was 0.54. ICC values were <0.50 for 71% of acylcarnitines, 48% of amino acids, 44% of biogenic amines, 36% of sphingomyelins, 34% of phosphatidylcholines and 33% of lysophosphatidylcholines. Overall, reproducibility was lower in non-fasting as compared to fasting samples, with a statistically significant difference for 19–36% of acylcarnitines, phosphatidylcholines and sphingomyelins. Conclusion A single measurement per individual may be sufficient for the study of 73% and 52% of the metabolites showing ICCs >0.50 in fasting and non-fasting samples, respectively. ICCs were higher in fasting samples that are preferable to non-fasting.
    PLoS ONE 08/2015; 10(8-8):e0135437. DOI:10.1371/journal.pone.0135437 · 3.23 Impact Factor
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    ABSTRACT: An improved understanding of the contribution of the diet to health and disease risks requires accurate assessments of dietary exposure in nutritional epidemiologic studies. The use of dietary biomarkers may improve the accuracy of estimates. We applied a metabolomic approach in a large cohort study to identify novel biomarkers of intake for a selection of polyphenol-containing foods. The large chemical diversity of polyphenols and their wide distribution over many foods make them ideal biomarker candidates for such foods. Metabolic profiles were measured with the use of high-resolution mass spectrometry in 24-h urine samples from 481 subjects from the large European Prospective Investigation on Cancer and Nutrition cohort. Peak intensities were correlated to acute and habitual dietary intakes of 6 polyphenol-rich foods (coffee, tea, red wine, citrus fruit, apples and pears, and chocolate products) measured with the use of 24-h dietary recalls and food-frequency questionnaires, respectively. Correlation (r > 0.3, p < 0.01 after correction for multiple testing) and discriminant [pcorr (1) > 0.3, VIP > 1.5] analyses showed that >2000 mass spectral features from urine metabolic profiles were significantly associated with the consumption of the 6 selected foods. More than 80 polyphenol metabolites associated with the consumption of the selected foods could be identified, and large differences in their concentrations reflecting individual food intakes were observed within and between 4 European countries. Receiver operating characteristic curves showed that 5 polyphenol metabolites, which are characteristic of 5 of the 6 selected foods, had a high predicting ability of food intake. Highly diverse food-derived metabolites (the so-called food metabolome) can be characterized in human biospecimens through this powerful metabolomic approach and screened to identify novel biomarkers for dietary exposures, which are ultimately essential to better understand the role of the diet in the cause of chronic diseases. © 2015 American Society for Nutrition.
    American Journal of Clinical Nutrition 08/2015; DOI:10.3945/ajcn.114.101881 · 6.77 Impact Factor
  • Journal of epidemiology and community health 08/2015; DOI:10.1136/jech-2015-206089 · 3.50 Impact Factor
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    ABSTRACT: Interest in the potential of DNA methylation in peripheral blood as a biomarker of cancer risk is increasing. We aimed to assess whether epigenome-wide DNA methylation measured in peripheral blood samples obtained before onset of the disease is associated with increased risk of breast cancer. We report on three independent prospective nested case-control studies from the European Prospective Investigation into Cancer and Nutrition (EPIC-Italy; n = 162 matched case-control pairs), the Norwegian Women and Cancer study (NOWAC; n = 168 matched pairs), and the Breakthrough Generations Study (BGS; n = 548 matched pairs). We used the Illumina 450k array to measure methylation in the EPIC and NOWAC cohorts. Whole-genome bisulphite sequencing (WGBS) was performed on the BGS cohort using pooled DNA samples, combined to reach 50× coverage across ~16 million CpG sites in the genome including 450k array CpG sites. Mean β values over all probes were calculated as a measurement for epigenome-wide methylation. In EPIC, we found that high epigenome-wide methylation was associated with lower risk of breast cancer (odds ratio (OR) per 1 SD = 0.61, 95 % confidence interval (CI) 0.47-0.80; -0.2 % average difference in epigenome-wide methylation for cases and controls). Specifically, this was observed in gene bodies (OR = 0.51, 95 % CI 0.38-0.69) but not in gene promoters (OR = 0.92, 95 % CI 0.64-1.32). The association was not replicated in NOWAC (OR = 1.03 95 % CI 0.81-1.30). The reasons for heterogeneity across studies are unclear. However, data from the BGS cohort was consistent with epigenome-wide hypomethylation in breast cancer cases across the overlapping 450k probe sites (difference in average epigenome-wide methylation in case and control DNA pools = -0.2 %). We conclude that epigenome-wide hypomethylation of DNA from pre-diagnostic blood samples may be predictive of breast cancer risk and may thus be useful as a clinical biomarker.
    08/2015; 7(1):67. DOI:10.1186/s13148-015-0104-2
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    ABSTRACT: 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 7 metabolites and 4 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. This article is protected by copyright. All rights reserved. © 2015 UICC.
    International Journal of Cancer 08/2015; DOI:10.1002/ijc.29718 · 5.09 Impact Factor
  • Cancer Research 08/2015; 75(15 Supplement):4615-4615. DOI:10.1158/1538-7445.AM2015-4615 · 9.33 Impact Factor
  • Cancer Research 08/2015; 75(15 Supplement):4614-4614. DOI:10.1158/1538-7445.AM2015-4614 · 9.33 Impact Factor
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    ABSTRACT: The crosstalk between microRNAs (miRNAs) and other epigenetic factors may lead to novel hypotheses about carcinogenesis identifying new targets for research. Since a single miRNA can regulate multiple downstream target genes, its altered expression may potentially be a sensitive biomarker to detect early malignant transformation and improve diagnosis and prognosis. In the current study, we tested the hypothesis that altered methylation of miRNA encoding genes, associated with deregulated mature miRNA expression, may be related to dietary and lifestyle factors and may contribute to cancer development.In a case-control study nested in a prospective cohort (EPIC-Italy), we analysed DNA methylation levels of miRNA encoding genes (2,191 CpG probes related to 517 genes) that are present in the Infinium Human Methylation450 BeadChip array in prediagnostic peripheral white blood cells of subjects who developed Colorectal Cancer (CRC, n=159) or Breast Cancer (BC, n=166) and matched subjects who remained clinically healthy.In the whole cohort, several differentially methylated miRNA genes were observed in association with age, sex, smoking habits and physical activity. Interestingly, in the case-control study, 8 differentially methylated miRNAs were identified in subjects who went on to develop BC (miR-328, miR-675, miR-1307, miR-1286, miR-1275, miR-1910, miR-24-1, and miR-548a-1; all Bonferroni-adjusted p-values < 0.05). No significant associations were found with CRC.Assuming that altered methylation of miRNAs detectable in blood may be present before diagnosis, it may represent a biomarker for early detection or risk of cancer and may help to understand the cascade of events preceding tumour onset. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email:
    Carcinogenesis 07/2015; 75(15 Supplement). DOI:10.1093/carcin/bgv102 · 5.33 Impact Factor
  • Miquel Porta · Paolo Vineis · Francisco Bolúmar
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    ABSTRACT: The current deconstruction of paradoxes is one among several signs that a profound renewal of methods for clinical and epidemiological research is taking place; perhaps for some basic life sciences as well. The new methodological approaches have already deconstructed and explained long puzzling apparent paradoxes, including the (non-existent) benefits of obesity in diabetics, or of smoking in low birth weight. Achievements of the new methods also comprise the elucidation of the causal structure of long-disputed and highly complex questions, as Berkson's bias and Simpson's paradox, and clarifying reasons for deep controversies, as those on estrogens and endometrial cancer, or on adverse effects of hormone replacement therapy. These are signs that the new methods can go deeper and beyond the methods in current use. A major example of a highly relevant idea is: when we condition on a common effect of a pair of variables, then a spurious association between such pair is likely. The implications of these ideas are potentially vast. A substantial number of apparent paradoxes may simply be the result of collider biases, a source of selection bias that is common not just in epidemiologic research, but in many types of research in the health, life, and social sciences. The new approaches develop a new framework of concepts and methods, as collider, instrumental variables, d-separation, backdoor path and, notably, Directed Acyclic Graphs (DAGs). The current theoretical and methodological renewal-or, perhaps, "revolution"-may be changing deeply how clinical and epidemiological research is conceived and performed, how we assess the validity and relevance of findings, and how causal inferences are made. Clinical and basic researchers, among others, should get acquainted with DAGs and related concepts.
    European Journal of Epidemiology 07/2015; DOI:10.1007/s10654-015-0068-8 · 5.34 Impact Factor
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    ABSTRACT: Metabolomics is a potentially powerful tool for identification of biomarkers associated with lifestyle exposures and risk of various diseases. This is the rationale of the 'meeting-in-the-middle' concept, for which an analytical framework was developed in this study. In a nested case-control study on hepatocellular carcinoma (HCC) within the European Prospective Investigation into Cancer and nutrition (EPIC), serum (1)H nuclear magnetic resonance (NMR) spectra (800 MHz) were acquired for 114 cases and 222 matched controls. Through partial least square (PLS) analysis, 21 lifestyle variables (the 'predictors', including information on diet, anthropometry and clinical characteristics) were linked to a set of 285 metabolic variables (the 'responses'). The three resulting scores were related to HCC risk by means of conditional logistic regressions. The first PLS factor was not associated with HCC risk. The second PLS metabolomic factor was positively associated with tyrosine and glucose, and was related to a significantly increased HCC risk with OR = 1.11 (95% CI: 1.02, 1.22, P = 0.02) for a 1SD change in the responses score, and a similar association was found for the corresponding lifestyle component of the factor. The third PLS lifestyle factor was associated with lifetime alcohol consumption, hepatitis and smoking, and had negative loadings on vegetables intake. Its metabolomic counterpart displayed positive loadings on ethanol, glutamate and phenylalanine. These factors were positively and statistically significantly associated with HCC risk, with 1.37 (1.05, 1.79, P = 0.02) and 1.22 (1.04, 1.44, P = 0.01), respectively. Evidence of mediation was found in both the second and third PLS factors, where the metabolomic signals mediated the relation between the lifestyle component and HCC outcome. This study devised a way to bridge lifestyle variables to HCC risk through NMR metabolomics data. This implementation of the 'meeting-in-the-middle' approach finds natural applications in settings characterised by high-dimensional data, increasingly frequent in the omics generation. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail:
    Mutagenesis 06/2015; DOI:10.1093/mutage/gev045 · 2.79 Impact Factor
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    Dataset: IJC2015
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    ABSTRACT: Indian Asians, who make up a quarter of the world's population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes. We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p<1 × 10(-7). We compared methylation levels between Indian Asian and European controls without type 2 diabetes at baseline to estimate the potential contribution of DNA methylation to increased risk of future type 2 diabetes incidence among Indian Asians. 1608 (11·9%) of 13 535 Indian Asians and 306 (4·3%) of 7066 Europeans developed type 2 diabetes over a mean of 8·5 years (SD 1·8) of follow-up. The age-adjusted and sex-adjusted incidence of type 2 diabetes was 3·1 times (95% CI 2·8-3·6; p<0·0001) higher among Indian Asians than among Europeans, and remained 2·5 times (2·1-2·9; p<0·0001) higher after adjustment for adiposity, physical activity, family history of type 2 diabetes, and baseline glycaemic measures. The mean absolute difference in methylation level between type 2 diabetes cases and controls ranged from 0·5% (SD 0·1) to 1·1% (0·2). Methylation markers at five loci were associated with future type 2 diabetes incidence; the relative risk per 1% increase in methylation was 1·09 (95% CI 1·07-1·11; p=1·3 × 10(-17)) for ABCG1, 0·94 (0·92-0·95; p=4·2 × 10(-11)) for PHOSPHO1, 0·94 (0·92-0·96; p=1·4 × 10(-9)) for SOCS3, 1·07 (1·04-1·09; p=2·1 × 10(-10)) for SREBF1, and 0·92 (0·90-0·94; p=1·2 × 10(-17)) for TXNIP. A methylation score combining results for the five loci was associated with future type 2 diabetes incidence (relative risk quartile 4 vs quartile 1 3·51, 95% CI 2·79-4·42; p=1·3 × 10(-26)), and was independent of established risk factors. Methylation score was higher among Indian Asians than Europeans (p=1 × 10(-34)). DNA methylation might provide new insights into the pathways underlying type 2 diabetes and offer new opportunities for risk stratification and prevention of type 2 diabetes among Indian Asians. The European Union, the UK National Institute for Health Research, the Wellcome Trust, the UK Medical Research Council, Action on Hearing Loss, the UK Biotechnology and Biological Sciences Research Council, the Oak Foundation, the Economic and Social Research Council, Helmholtz Zentrum Munchen, the German Research Center for Environmental Health, the German Federal Ministry of Education and Research, the German Center for Diabetes Research, the Munich Center for Health Sciences, the Ministry of Science and Research of the State of North Rhine-Westphalia, and the German Federal Ministry of Health. Copyright © 2015 Elsevier Ltd. All rights reserved.
    06/2015; 3(7). DOI:10.1016/S2213-8587(15)00127-8
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    ABSTRACT: Long-term exposure to particulate matter (PM) has been associated with increased cardiovascular morbidity and mortality but little is known about the role of the chemical composition of PM. This study examined the association of residential long-term exposure to PM components with incident coronary events. Eleven cohorts from Finland, Sweden, Denmark, Germany, and Italy participated in this analysis. 5,157 incident coronary events were identified within 100,166 persons followed on average for 11.5 years. Long-term residential concentrations of PM < 10 μm (PM10), PM < 2.5 μm (PM2.5), and a priori selected constituents (copper, iron, nickel, potassium, silicon, sulfur, vanadium, and zinc) were estimated with land-use regression models. We used Cox proportional hazard models adjusted for a common set of confounders to estimate cohort-specific component effects with and without including PM mass, and random effects meta-analyses to pool cohort-specific results. A 100 ng/m³ increase in PM10 K and a 50 ng/m³ increase in PM2.5 K were associated with a 6% (hazard ratio and 95% confidence interval: 1.06 [1.01, 1.12]) and 18% (1.18 [1.06, 1.32]) increase in coronary events. Estimates for PM10 Si and PM2.5 Fe were also elevated. All other PM constituents indicated a positive association with coronary events. When additionally adjusting for PM mass, the estimates decreased except for K. This multicenter study of 11 European cohorts pointed to an association between long-term exposure to PM constituents and coronary events, especially for indicators of road dust.
    Epidemiology (Cambridge, Mass.) 05/2015; 26(4). DOI:10.1097/EDE.0000000000000300 · 6.20 Impact Factor
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    ABSTRACT: The relationship between coffee consumption and coronary heart disease (CHD) has been investigated in several studies with discrepant results. We examined the association between Italian-style (espresso and mocha) coffee consumption and CHD risk. We investigated 12,800 men and 30,449 women without history of cardiovascular disease recruited to the EPICOR prospective cohort study. Coffee consumption was assessed at baseline. In a random sub-cohort of 1472 subjects, plasma triglycerides, and total, LDL and HDL cholesterol were determined to investigate the effect of coffee consumption on plasma lipids. After a mean follow up of 10.9 years, 804 cases of CHD (500 acute events, 56 fatal events and 248 revascularizations, all first events) were identified. Multivariable adjusted hazard ratios for CHD were: 1.18 (95% CI 0.87-1.60) for drinking 1-2 cups/day, 1.37 (95% CI 1.03-1.82) for >2-4 cups/day and 1.52 (95% CI 1.11-2.07) for over 4 cups/day (P trend <0.001) compared to reference (<1 cup/day). Plasma triglycerides, and total, LDL and HDL cholesterol did not vary significantly (ANOVA) with coffee consumption. Consumption of over 2 cups/day of Italian-style coffee is associated with increased CHD risk, but coffee consumption was not associated with plasma lipid changes, so the adverse effect of consumption appears unrelated to lipid profile.
    PLoS ONE 05/2015; 10(5):e0126550. DOI:10.1371/journal.pone.0126550 · 3.23 Impact Factor

Publication Stats

20k Citations
3,969.25 Total Impact Points


  • 2014–2015
    • National Cancer Institute (USA)
      • • Division of Cancer Epidemiology and Genetics
      • • Radiation Epidemiology
      베서스다, Maryland, United States
    • Centre d'Immunologie de Marseille-Luminy
      Marsiglia, Provence-Alpes-Côte d'Azur, France
  • 2004–2015
    • Imperial College London
      • • Department of Epidemiology and Biostatistics
      • • Faculty of Medicine
      Londinium, England, United Kingdom
    • CRO Centro di Riferimento Oncologico di Aviano
      Aviano, Friuli Venezia Giulia, Italy
  • 2011–2014
    • Human Genetics Foundation Torino
      Torino, Piedmont, Italy
    • Change Institute
      Londinium, England, United Kingdom
  • 2004–2014
    • Utrecht University
      • Institute for Risk Assessment Sciences (IRAS)
      Utrecht, Utrecht, Netherlands
  • 1992–2014
    • Università degli Studi di Torino
      • • Dipartimento di Biotecnologie Molecolari e Scienze per la Salute
      • • Department of Medical Science
      Torino, Piedmont, Italy
  • 2013
    • National Institutes of Health
      • Division of Cancer Epidemiology and Genetics
      베서스다, Maryland, United States
  • 2012
    • University of Bristol
      • School of Experimental Psychology
      Bristol, England, United Kingdom
    • University of Oxford
      • Cancer Epidemiology Unit
      Oxford, ENG, United Kingdom
  • 2011–2012
    • Catalan Institute of Oncology
      • • Nutrition, Environment and Cancer Unit
      • • Cancer Epidemiology Research Programme (PREC)
      Badalona, Catalonia, Spain
  • 2008–2011
    • International Agency for Research on Cancer
      Lyons, Rhône-Alpes, France
    • Lund University
      • Department of Occupational and Environmental Medicine
      Lund, Skane, Sweden
  • 2003–2011
    • ISI Foundation
      Torino, Piedmont, Italy
    • Ospedale San Giovanni Battista, ACISMOM
      Torino, Piedmont, Italy
    • Centro di Riferimento per l'Epidemiologia e la Prevenzione Oncologica in Piemonte
      Torino, Piedmont, Italy
  • 2010
    • Academy of Athens
      Athínai, Attica, Greece
  • 2008–2009
    • Imperial Valley College
      Imperial, California, United States
  • 2007
    • University of Naples Federico II
      Napoli, Campania, Italy
    • Umeå University
      Umeå, Västerbotten, Sweden
  • 2000–2004
    • Memorial Sloan-Kettering Cancer Center
      • Epidemiology & Biostatistics Group
      New York, New York, United States
  • 2001
    • London School of Hygiene and Tropical Medicine
      Londinium, England, United Kingdom
    • Università degli Studi di Siena
      Siena, Tuscany, Italy
  • 1993
    • Rhein Main Medical Center
      Wiesbaden, Hesse, Germany