13 results found
Chadeau M, Jain P, Vineis P, et al., 2018, A multivariate approach to investigate the combined biological effects of multiple exposures, Journal of Epidemiology and Community Health, Vol: 72, Pages: 564-571, ISSN: 0143-005X
Epidemiological studies provide evidence that environmental exposures may affect health through complex mixtures. Formal investigation of the effect of exposure mixtures is usually achieved by modelling interactions, which relies on strong assumptions relating to the identity and the number of the exposures involved in such interactions, and on the order and parametric form of these interactions. These hypotheses become difficult to formulate and justify in an exposome context, where influential exposures are numerous and heterogeneous. To capture both the complexity of the exposome, and its possibly pleiotropic effects, models handling multivariate predictors and responses, such as partial least squares (PLS) algorithms, can prove useful. As an illustrative example, we applied PLS models to data from a study investigating the inflammatory response (blood concentration of 13 immune markers) to the exposure to four disinfection by-products (one brominated and three chlorinated compounds), while swimming in a pool. To accommodate the multiple observations per participant (N=60; before and after the swim), we adopted a multi-level extension of the PLS algorithms, including sparse PLS models shrinking loadings coefficients of unimportant predictors (exposures), and/or responses (protein levels). Despite the strong correlation among co-occurring exposures, our approach identified a subset of exposures (N=3/4) affecting the exhaled levels of 8 (out of 13) immune markers. PLS algorithms can easily scale to high-dimensional exposures and responses, and prove useful for exposome research to identify sparse sets of exposures jointly affecting a set of (selected) biological markers. Our descriptive work may guide these extensions for higher dimensional data.
Chadeau M, van Veldhoven, Keski-Rahkonen P, et al., 2017, Effects of exposure to water Disinfection By-Products in a swimming pool: A metabolome-wide association study, Environment International, Vol: 111, Pages: 60-70, ISSN: 0160-4120
BackgroundExposure to disinfection by-products (DBPs) in drinking water and chlorinated swimming pools are associated with adverse health outcomes, but biological mechanisms remain poorly understood.ObjectivesEvaluate short-term changes in metabolic profiles in response to DBP exposure while swimming in a chlorinated pool.Materials and methodsThe PISCINA-II study (EXPOsOMICS project) includes 60 volunteers swimming 40 min in an indoor pool. Levels of most common DBPs were measured in water and in exhaled breath before and after swimming. Blood samples, collected before and 2 h after swimming, were used for metabolic profiling by liquid-chromatography coupled to high-resolution mass-spectrometry. Metabolome-wide association between DBP exposures and each metabolic feature was evaluated using multivariate normal (MVN) models. Sensitivity analyses and compound annotation were conducted.ResultsExposure levels of all DBPs in exhaled breath were higher after the experiment. A total of 6,471 metabolic features were detected and 293 features were associated with at least one DBP in exhaled breath following Bonferroni correction. A total of 333 metabolic features were associated to at least one DBP measured in water or urine. Uptake of DBPs and physical activity were strongly correlated and mutual adjustment reduced the number of statistically significant associations. From the 293 features, 20 could be identified corresponding to 13 metabolites including compounds in the tryptophan metabolism pathway.ConclusionOur study identified numerous molecular changes following a swim in a chlorinated pool. While we could not explicitly evaluate which experiment-related factors induced these associations, molecular characterization highlighted metabolic features associated with exposure changes during swimming.
van veldhoven K, Polidoro S, Baglietto L, et al., 2015, Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis, Clinical Epigenetics, Vol: 7, ISSN: 1868-7083
Background. 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.Methods. 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 50x-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.Results. In EPIC we found that high epigenome-wide methylation was associated with lower risk of breast cancer (OR per 1SD=0.61, 95%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%).Conclusions. 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.
Stringhini S, Polidoro S, Sacerdote C, et al., 2015, Life-course socioeconomic status and DNA methylation of genes regulating inflammation, INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, Vol: 44, Pages: 1320-1330, ISSN: 0300-5771
Demetriou CA, van Veldhoven K, Relton C, et al., 2015, Biological embedding of early-life exposures and disease risk in humans: a role for DNA methylation, EUROPEAN JOURNAL OF CLINICAL INVESTIGATION, Vol: 45, Pages: 303-332, ISSN: 0014-2972
Tsilidis KK, Capothanassi D, Allen NE, et al., 2014, Metformin does not affect cancer risk: a cohort study in the UK clinical practice research datalink analyzed like an intention-to-treat trial, Diabetes Care, Vol: 37, Pages: 2522-2532, ISSN: 0149-5992
OBJECTIVE Meta-analyses of epidemiologic studies have suggested that metformin may reduce cancer incidence, but randomized controlled trials did not support this hypothesis.RESEARCH DESIGN AND METHODS A retrospective cohort study, Clinical Practice Research Datalink, was designed to investigate the association between use of metformin compared with other antidiabetes medications and cancer risk by emulating an intention-to-treat analysis as in a trial. A total of 95,820 participants with type 2 diabetes who started taking metformin and other oral antidiabetes medications within 12 months of their diagnosis (initiators) were followed up for first incident cancer diagnosis without regard to any subsequent changes in pharmacotherapy. Cox proportional hazards models were used to estimate multivariable-adjusted hazard ratios (HR) and 95% CI.RESULTS A total of 51,484 individuals (54%) were metformin initiators and 18,264 (19%) were sulfonylurea initiators, and 3,805 first incident cancers were diagnosed during a median follow-up time of 5.1 years. Compared with initiators of sulfonylurea, initiators of metformin had a similar incidence of total cancer (HR 0.96; 95% CI 0.89–1.04) and colorectal (HR 0.92; 95% CI 0.76–1.13), prostate (HR 1.02; 95% CI 0.83–1.25), lung (HR 0.85; 95% CI 0.68–1.07), or postmenopausal breast (HR 1.03; 95% CI 0.82–1.31) cancer or any other cancer.CONCLUSIONS In this large study, individuals with diabetes who used metformin had a similar risk of developing cancer compared with those who used sulfonylureas.
van Veldhoven K, Rahman S, Vineis P, 2014, Epigenetics and epidemiology: models of study and examples., Pages: 241-255
Epidemiological studies have successfully identified several environmental causes of disease, but often these studies are limited by methodological problems (e.g. lack of sensitivity and specificity in exposure assessment; confounding). Proposed approaches to improve observational studies of environmental associations are Mendelian randomization and the meet-in-the-middle (MITM) approach. The latter uses signals from the growing field of -omics as putative intermediate biomarkers in the pathogenetic process that links exposure with disease. The first part of this approach consists in the association between exposure and disease. The next step consists in the study of the relationship between (biomarkers of) exposure and intermediate -omic biomarkers of early effect; thirdly, the relation between the disease outcome and intermediate -omic biomarkers is assessed. We propose that when an association is found in all three steps it is possible that there is a casual association. One of the associations that have been investigated extensively in the recent years but is not completely understood is that between environmental endocrine disruptors and breast cancer. Here we present an example of how the "meet-in-the-middle" approach can be used to address the role of endocrine disruptors, by reviewing the relevant literature.
Demetriou CA, Chen J, Polidoro S, et al., 2013, Methylome Analysis and Epigenetic Changes Associated with Menarcheal Age, PLOS One, Vol: 8, ISSN: 1932-6203
Reproductive factors have been linked to both breast cancer and DNA methylation, suggesting methylation as an importantmechanism by which reproductive factors impact on disease risk. However, few studies have investigated the link betweenreproductive factors and DNA methylation in humans. Genome-wide methylation in peripheral blood lymphocytes of 376healthy 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-Italysub-cohort, using the Infinium HumanMethylation 450 BeadChip. Multivariate logistic regression and linear models wereused 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 eachyearly 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-responserelationship with LUMA methylation levels (OR12–14vs.#11 yrs:1.78, 95%CI:1.01–3.17 and OR$15vs.#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 notsignificantly associated with menarcheal age. In locus by locus comparative analyses, only one CpG site had significantlydifferent methylation depending on the menarcheal age category examined, but this finding was not replicated bypyrosequencing in an independent data set. This study suggests a link between age at menarche and genome wide DNAmethylation, and the difference in results between the two arrays suggests that repetitive element methylation has a role inthe association. Epigenetic changes may be modulated by menarcheal age, or the associatio
Herceg Z, Lambert M-P, van Veldhoven K, et al., 2013, Towards incorporating epigenetic mechanisms into carcinogen identification and evaluation, CARCINOGENESIS, Vol: 34, Pages: 1955-1967, ISSN: 0143-3334
Shenker NS, Ueland PM, Polidoro S, et al., 2013, DNA Methylation as a Long-term Biomarker of Exposure to Tobacco Smoke, EPIDEMIOLOGY, Vol: 24, Pages: 712-716, ISSN: 1044-3983
Vineis P, van Veldhoven K, Chadeau-Hyam M, et al., 2013, Advancing the application of omics-based biomarkers in environmental epidemiology, ENVIRONMENTAL AND MOLECULAR MUTAGENESIS, Vol: 54, Pages: 461-467, ISSN: 0893-6692
Shenker NS, Polidoro S, van Veldhoven K, et al., 2013, Epigenome-wide association study in the European Prospective Investigation into Cancer and Nutrition (EPIC-Turin) identifies novel genetic loci associated with smoking, HUMAN MOLECULAR GENETICS, Vol: 22, Pages: 843-851, ISSN: 0964-6906
Khan AE, van Veldhoven CM, Vineis P, 2011, Physical activity and lymphoid neoplasms in the European Prospective Investigation into Cancer and nutrition (EPIC), European Journal of Cancer, Vol: 47, Pages: 748-760
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