Publications
200 results found
Mostafavi N, Vlaanderen J, Portengen L, et al., 2017, Associations between genome-wide gene expression and ambient nitrogen Oxides, EPIDEMIOLOGY, Vol: 28, Pages: 320-328, ISSN: 1044-3983
Background: We hypothesize that biological perturbations due to exposure to ambient air pollution are reflected in gene expression levels in peripheral blood mononuclear cells.Methods: We assessed the association between exposure to ambient air pollution and genome-wide gene expression levels in peripheral blood mononuclear cells collected from 550 healthy subjects participating in cohorts from Italy and Sweden. Annual air pollution estimates of nitrogen oxides (NOx) at time of blood collection (1990–2006) were available from the ESCAPE study. In addition to univariate analysis and two variable selection methods to investigate the association between expression and exposure to NOx, we applied gene set enrichment analysis to assess overlap between our most perturbed genes and gene sets hypothesized to be related to air pollution and cigarette smoking. Finally, we assessed associations between NOx and CpG island methylation at the identified genes.Results: Annual average NOx exposure in the Italian and Swedish cohorts was 94.2 and 6.7 µg/m3, respectively. Long-term exposure to NOx was associated with seven probes in the Italian cohort and one probe in the Swedish (and combined) cohorts. For genes AHCYL2 and MTMR2, changes were also seen in the methylome. Genes hypothesized to be downregulated due to cigarette smoking were enriched among the most strongly downregulated genes from our study.Conclusion: This study provides evidence of subtle changes in gene expression related to exposure to long-term NOx. On a global level, the observed changes in the transcriptome may indicate similarities between air pollution and tobacco induced changes in the transcriptome.
Stringhini S, Carmeli C, Jokela M, et al., 2017, Socioeconomic status and the 25 x 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1.7 million men and women, The Lancet, Vol: 389, Pages: 1229-1237, ISSN: 0140-6736
Background:In 2011, WHO member states signed up to the 25 × 25 initiative, a plan to cut mortality due to non-communicable diseases by 25% by 2025. However, socioeconomic factors influencing non-communicable diseases have not been included in the plan. In this study, we aimed to compare the contribution of socioeconomic status to mortality and years-of-life-lost with that of the 25 × 25 conventional risk factors.Methods:We did a multicohort study and meta-analysis with individual-level data from 48 independent prospective cohort studies with information about socioeconomic status, indexed by occupational position, 25 × 25 risk factors (high alcohol intake, physical inactivity, current smoking, hypertension, diabetes, and obesity), and mortality, for a total population of 1 751 479 (54% women) from seven high-income WHO member countries. We estimated the association of socioeconomic status and the 25 × 25 risk factors with all-cause mortality and cause-specific mortality by calculating minimally adjusted and mutually adjusted hazard ratios [HR] and 95% CIs. We also estimated the population attributable fraction and the years of life lost due to suboptimal risk factors.Findings:During 26·6 million person-years at risk (mean follow-up 13·3 years [SD 6·4 years]), 310 277 participants died. HR for the 25 × 25 risk factors and mortality varied between 1·04 (95% CI 0·98–1·11) for obesity in men and 2 ·17 (2·06–2·29) for current smoking in men. Participants with low socioeconomic status had greater mortality compared with those with high socioeconomic status (HR 1·42, 95% CI 1·38–1·45 for men; 1·34, 1·28–1·39 for women); this association remained significant in mutually adjusted models that included the 25 × 25 factors (HR 1·26, 1·21–1·32, men and women combined). The population attrib
Vlaanderen J, Leenders M, Chadeau-Hyam M, et al., 2017, Exploring the nature of prediagnostic blood transcriptome markers of chronic lymphocytic leukemia by assessing their overlap with the transcriptome at the clinical stage, BMC GENOMICS, Vol: 18, ISSN: 1471-2164
Background:We recently identified 700 genes whose expression levels were predictive of chronic lymphocytic leukemia (CLL) in a genome-wide gene expression analysis of prediagnostic blood from future cases and matched controls. We hypothesized that a large fraction of these markers were likely related to early disease manifestations. Here we aim to gain a better understanding of the natural history of the identified markers by comparing results from our prediagnostic analysis, the only prediagnostic analysis to date, to results obtained from a meta-analysis of a series of publically available transcriptomics profiles obtained in incident CLL cases and controls.Results:We observed considerable overlap between the results from our prediagnostic study and the clinical CLL signals (p-value for overlap Bonferroni significant markers 0.01; p-value for overlap nominal significant markers < 2.20e-16). We observed similar patterns with time to diagnosis and similar functional annotations for the markers that were identified in both settings compared to the markers that were only identified in the prediagnostic study. These results suggest that both gene sets operate in similar pathways.Conclusion:An overlap exists between expression levels of genes predictive of CLL identified in prediagnostic blood and expression levels of genes associated to CLL at the clinical stage. Our analysis provides insight in a set of genes for which expression levels can be used to follow the time-course of the disease; providing an opportunity to study CLL progression in more detail in future studies.
Chatziioannou A, Georgiadis P, Hebels DG, et al., 2017, Blood-based omic profiling supports female susceptibility to tobacco smoke-induced cardiovascular diseases, SCIENTIFIC REPORTS, Vol: 7, ISSN: 2045-2322
We recently reported that differential gene expression and DNA methylation profiles in blood leukocytes of apparently healthy smokers predicts with remarkable efficiency diseases and conditions known to be causally associated with smoking, suggesting that blood-based omic profiling of human populations may be useful for linking environmental exposures to potential health effects. Here we report on the sex-specific effects of tobacco smoking on transcriptomic and epigenetic features derived from genome-wide profiling in white blood cells, identifying 26 expression probes and 92 CpG sites, almost all of which are affected only in female smokers. Strikingly, these features relate to numerous genes with a key role in the pathogenesis of cardiovascular disease, especially thrombin signaling, including the thrombin receptors on platelets F2R (coagulation factor II (thrombin) receptor; PAR1) and GP5 (glycoprotein 5), as well as HMOX1 (haem oxygenase 1) and BCL2L1 (BCL2-like 1) which are involved in protection against oxidative stress and apoptosis, respectively. These results are in concordance with epidemiological evidence of higher female susceptibility to tobacco-induced cardiovascular disease and underline the potential of blood-based omic profiling in hazard and risk assessment.
Kelly RS, Kiviranta H, Bergdahl IA, et al., 2017, Prediagnostic plasma concentrations of organochlorines and risk of B-cell non-Hodgkin lymphoma in envirogenomarkers: a nested case-control study, ENVIRONMENTAL HEALTH, Vol: 16, ISSN: 1476-069X
Background:Evidence suggests a largely environmental component to non-Hodgkin’s lymphoma (NHL). Persistent organic pollutants (POPs) including polychlorinated biphenyls (PCBs), DDE and HCB have been repeatedly implicated, but the literature is inconsistent and a causal relationship remains to be determined.Methods:The EnviroGenoMarkers study is nested within two prospective cohorts EPIC-Italy and the Northern Sweden Health and Disease Study. Six PCB congeners, DDE and HCB were measured in blood plasma samples provided at recruitment using gas-chromatography mass spectrometry. During 16 years follow-up 270 incident cases of B-cell NHL (including 76 cases of multiple myeloma) were diagnosed. Cases were matched to 270 healthy controls by centre, age, gender and date of blood collection. Cases were categorised into ordered quartiles of exposure for each POP based on the distribution of exposure in the control population. Logistic regression was applied to assess the association with risk, multivariate and stratified analyses were performed to identify confounders or effect modifiers.Results:The exposures displayed a strong degree of correlation, particularly amongst those PCBs with similar degrees of chlorination. There was no significant difference (p < 0.05) in median exposure levels between cases and controls for any of the investigated exposures. However under a multivariate model PCB138, PCB153, HCB and DDE displayed significant inverse trends (Wald test p-value <0.05). Under stratified analyses these were determined to be driven by males and by the Diffuse Large B-Cell Lymphoma subtype. When considering those in the highest levels of exposure (>90th percentile) the association was null for all POPsConclusion:We report no evidence that a higher body burden of PCBs, DDE or HCB increased the risk of subsequent NHL diagnosis. Significantly inverse associations were noted for males with a number of the investigated POPs. We hypothesize thes
Castagné R, Kelly-Irving M, Campanella G, et al., 2016, Biological marks of early-life socioeconomic experience is detected in the adult inflammatory transcriptome, Scientific Reports, Vol: 6, ISSN: 2045-2322
Consistent evidence is accumulating to link lower socioeconomic position (SEP) and poorer health, and the inflammatory system stands out as a potential pathway through which socioeconomic environment is biologically embedded. Using bloodderived genome-wide transcriptional profiles from 268 Italian participants of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we evaluated the association between early life, young and later adulthood SEP and the expression of 845 genes involved in human inflammatory responses. These were examined individually and jointly using several inflammatory scores. Our results consistently show that participants whose father had a manual (as compared to nonmanual) occupation exhibit, later in life, a higher inflammatory score, hence indicating an overall increased level of expression for the selected inflammatory-related genes. Adopting a life course approach, these associations remained statistically significant upon adjustment for later-in-life socioeconomic experiences. Sensitivity analyses indicated that our findings were not affected by the way the inflammatory score was calculated, and were replicated in an independent study. Our study provides additional evidence that childhood SEP is associated with a sustainable upregulation of the inflammatory transcriptome, independently of subsequent socioeconomic experiences. Our results support the hypothesis that early social inequalities impacts adult physiology.
Escher BI, Hackermuller J, Polte T, et al., 2016, From the exposome to mechanistic understanding of chemical-induced adverse effects., Environment International, Vol: 99, Pages: 97-106, ISSN: 0160-4120
The exposome encompasses an individual's exposure to exogenous chemicals, as well as endogenous chemicals that are produced or altered in response to external stressors. While the exposome concept has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. Here, we explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept that structures and organizes the sequence of biological events from an initial molecular interaction of a chemical with a biological target to an adverse outcome. Complementing exposome research with the AOP concept may facilitate a mechanistic understanding of stress-induced adverse effects, examine the relative contributions from various components of the exposome, determine the primary risk drivers in complex mixtures, and promote an integrative assessment of chemical risks for both human and environmental health.
Baglietto L, Ponzi E, Haycock P, et al., 2016, DNA methylation changes measured in pre-diagnostic peripheral blood samples are associated with smoking and lung cancer risk, International Journal of Cancer, Vol: 140, Pages: 50-61, ISSN: 1097-0215
DNA methylation changes are associated with cigarette smoking. We used the Illumina Infinium HumanMethylation450 array to determine whether methylation in DNA from pre-diagnostic, peripheral blood samples is associated with lung cancer risk. We used a case-control study nested within the EPIC-Italy cohort and a study within the MCCS cohort as discovery sets (a total of 552 case-control pairs). We validated the top signals in 429 case-control pairs from another 3 studies. We identified six CpGs for which hypomethylation was associated with lung cancer risk: cg05575921 in the AHRR gene (p-valuepooled = 4x10(-17) ), cg03636183 in the F2RL3 gene (p-valuepooled = 2x10(-13) ), cg21566642 and cg05951221 in 2q37.1 (p-valuepooled = 7x10(-16) and 1x10(-11) respectively), cg06126421 in 6p21.33 (p-valuepooled = 2x10(-15) ) and cg23387569 in 12q14.1 (p-valuepooled = 5x10(-7) ). For cg05951221 and cg23387569 the strength of association was virtually identical in never and current smokers. For all these CpGs except for cg23387569, the methylation levels were different across smoking categories in controls (p-valuesheterogeneity ≤ 1.8 x10(-7) ), were lowest for current smokers and increased with time since quitting for former smokers. We observed a gain in discrimination between cases and controls measured by the area under the ROC curve of at least 8% (p-values ≥ 0.003) in former smokers by adding methylation at the 6 CpGs into risk prediction models including smoking status and number of pack-years. Our findings provide convincing evidence that smoking and possibly other factors lead to DNA methylation changes measurable in peripheral blood that may improve prediction of lung cancer risk. This article is protected by copyright. All rights reserved.
Vineis P, Chadeau-Hyam M, Gmuender H, et al., 2016, The exposome in practice: Design of the EXPOsOMICS project, International Journal of Hygiene and Environmental Health, Vol: 220, Pages: 142-151, ISSN: 1618-131X
EXPOsOMICS is a European Union funded project that aims to develop a novel approach to the assessment of exposure to high priority environmental pollutants, by characterizing the external and the internal components of the exposome. It focuses on air and water contaminants during critical periods of life. To this end, the project centres on 1) exposure assessment at the personal and population levels within existing European short and long-term population studies, exploiting available tools and methods which have been developed for personal exposure monitoring (PEM); and 2) multiple "omic" technologies for the analysis of biological samples (internal markers of external exposures). The search for the relationships between external exposures and global profiles of molecular features in the same individuals constitutes a novel advancement towards the development of "next generation exposure assessment" for environmental chemicals and their mixtures. The linkage with disease risks opens the way to what are defined here as 'exposome-wide association studies' (EWAS).
Agier L, Portengen L, Chadeau-Hyam M, et al., 2016, A systematic comparison of linear regression-based statistical methods to assess exposome-health associations, Environ Health Perspect, Vol: 124, Pages: 1848-1856, ISSN: 0091-6765
BACKGROUND: The exposome constitutes a promising framework to better understand the effect of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. OBJECTIVES: We compared the performances of linear regression-based statistical methods in assessing exposome-health associations. METHODS: In a simulation study, we generated 237 exposure covariates with a realistic correlation structure, and a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. RESULTS: On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and a FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm a sensitivity of 80% and a FDP of 33%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%), despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. CONCLUSIONS: Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study are limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. While GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods.
Castagné R, Delpierre C, Kelly-Irving M, et al., 2016, A life course approach to explore the biological embedding of socioeconomic position and social mobility through circulating inflammatory markers, Scientific Reports, Vol: 6, ISSN: 2045-2322
Lower socioeconomic position (SEP) has consistently been associated with poorer health. To explore potential biological embedding and the consequences of SEP experiences from early life to adulthood, we investigate how SEP indicators at different points across the life course may be related to a combination of 28 inflammation markers. Using blood-derived inflammation profiles measured by a multiplex array in 268 participants from the Italian component of the European Prospective Investigation into Cancer and Nutrition cohort, we evaluate the association between early life, young adulthood and later adulthood SEP with each inflammatory markers separately, or by combining them into an inflammatory score. We identified an increased inflammatory burden in participants whose father had a manual occupation, through increased plasma levels of CSF3 (G-CSF; β = 0.29; P = 0.002), and an increased inflammatory score (β = 1.96; P = 0.029). Social mobility was subsequently modelled by the interaction between father’s occupation and the highest household occupation, revealing a significant difference between “stable Non-manual” profiles over the life course versus “Manual to Non-manual” profiles (β = 2.38, P = 0.023). Low SEP in childhood is associated with modest increase in adult inflammatory burden; however, the analysis of social mobility suggests a stronger effect of an upward social mobility over the life course.
Georgiadis P, Hebels DG, Valavanis I, et al., 2016, Omics for prediction of environmental health effects: blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking, Scientific Reports, Vol: 6, ISSN: 2045-2322
The utility of blood-based omic profiles for linking environmental exposures to their potential health effects was evaluated in 649 individuals, drawn from the general population, in relation to tobacco smoking, an exposure with well-characterised health effects. Using disease connectivity analysis, we found that the combination of smoking-modified, genome-wide gene (including miRNA) expression and DNA methylation profiles predicts with remarkable reliability most diseases and conditions independently known to be causally associated with smoking (indicative estimates of sensitivity and positive predictive value 94% and 84%, respectively). Bioinformatics analysis reveals the importance of a small number of smoking-modified, master-regulatory genes and suggest a central role for altered ubiquitination. The smoking-induced gene expression profiles overlap significantly with profiles present in blood cells of patients with lung cancer or coronary heart disease, diseases strongly associated with tobacco smoking. These results provide proof-of-principle support to the suggestion that omic profiling in peripheral blood has the potential of identifying early, disease-related perturbations caused by toxic exposures and may be a useful tool in hazard and risk assessment.
Liquet B, Bottolo L, Campanella G, et al., 2016, R2GUESS: a graphics processing unit-based R package for Bayesian variable selection regression of multivariate responses, Journal of Statistical Software, Vol: 69, ISSN: 1548-7660
Technological advances in molecular biology over the past decade have given rise to high dimensional and complex datasets offering the possibility to investigate biological associations between a range of genomic features and complex phenotypes. The analysis of this novel type of data generated unprecedented computational challenges which ultimately led to the definition and implementation of computationally efficient statistical models that were able to scale to genome-wide data, including Bayesian variable selection approaches. While extensive methodological work has been carried out in this area, only few methods capable of handling hundreds of thousands of predictors were implemented and distributed. Among these we recently proposed GUESS, a computationally optimised algorithm making use of graphics processing unit capabilities, which can accommodate multiple outcomes. In this paper we propose R2GUESS, an R package wrapping the original C++ source code. In addition to providing a user-friendly interface of the original code automating its parametrisation, and data handling, R2GUESS also incorporates many features to explore the data, to extend statistical inferences from the native algorithm (e.g., effect size estimation, significance assessment), and to visualize outputs from the algorithm. We first detail the model and its parametrisation, and describe in details its optimised implementation. Based on two examples we finally illustrate its statistical performances and flexibility.
Hosnijeh FS, Portengen L, Spath F, et al., 2016, Soluble B-cell activation marker of sCD27 and sCD30 and future risk of B-cell lymphomas: A nested case-control study and meta-analyses, International Journal of Cancer, Vol: 138, Pages: 2357-2367, ISSN: 1097-0215
Prediagnostic serum/plasma concentrations of B-cell activation markers have been associated with future risk of B-cell lymphomas (BCL) in HIV-infected patients and in the general population. Current evidence for the general population is however limited and relies on relatively small numbers of observations, especially for specific histologies. We carried out a nested case-control study, including 218 BCL and 218 matched controls, within two prospective cohorts, to investigate the association between plasma levels of soluble (s)CD27 and sCD30 and future risk of BCL, and main histologic subtypes separately. To expand the evidence further, we performed meta-analyses of the published data on these associations from prospective studies among the general population. Our study revealed a significant relationship between sCD30 concentration and BCL risk (OR = 0.86, 1.53, 1.76, for the 2nd–4th quartiles respectively, p trend = 0.01). Similar increased risks were observed for diffuse large B-cell lymphoma and follicular lymphoma. Analyses of sCD27 blood concentrations did not show significant associations with BCL, (OR = 0.90, 1.26, 1.65 for the 2nd–4th quartiles, respectively, p trend = 0.17), but significant associations were observed for chronic lymphocytic leukaemia and for the group of “other BCL” subtypes. Our findings involving sCD30 were confirmed within our meta-analyses of five prospective cohorts, while results were more heterogeneous for sCD27 with the exception of CLL which was found consistently in all studies. Data to date suggest that chronic B-cell stimulation might be an important mechanism involved in B-cell lymphomagenesis both in HIV-infected and in the general population.
Fasanelli F, Baglietto L, Ponzi E, et al., 2015, Hypomethylation of smoking-related genes is associated with future lung cancer in four prospective cohorts, Nature Communications, Vol: 6, ISSN: 2041-1723
DNA hypomethylation in certain genes is associated with tobacco exposure but it is unknown whether these methylation changes translate into increased lung cancer risk. In an epigenome-wide study of DNA from pre-diagnostic blood samples from 132 case–control pairs in the NOWAC cohort, we observe that the most significant associations with lung cancer risk are for cg05575921 in AHRR (OR for 1 s.d.=0.37, 95% CI: 0.31–0.54, P-value=3.3 × 10−11) and cg03636183 in F2RL3 (OR for 1 s.d.=0.40, 95% CI: 0.31–0.56, P-value=3.9 × 10−10), previously shown to be strongly hypomethylated in smokers. These associations remain significant after adjustment for smoking and are confirmed in additional 664 case–control pairs tightly matched for smoking from the MCCS, NSHDS and EPIC HD cohorts. The replication and mediation analyses suggest that residual confounding is unlikely to explain the observed associations and that hypomethylation of these CpG sites may mediate the effect of tobacco on lung cancer risk.
Kato N, Loh M, Takeuchi F, et al., 2015, Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation, Nature Genetics, Vol: 47, Pages: 1282-1293, ISSN: 1546-1718
We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10−11 to 5.0 × 10−21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10−6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.
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.
Campanella G, Polidoro S, Di Gaetano C, et al., 2015, Epigenetic signatures of internal migration in Italy, INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, Vol: 44, Pages: 1442-1449, ISSN: 0300-5771
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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
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Assi N, Fages A, Vineis P, et al., 2015, A statistical framework to model the meeting-in-the-middle principle using metabolomic data: application to hepatocellular carcinoma in the EPIC study, Mutagenesis, Vol: 30, Pages: 743-753, ISSN: 1464-3804
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 1H 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 ‘meet
Chambers JC, Loh M, Lehne B, et al., 2015, Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study, The Lancet Diabetes & Endocrinology, Vol: 3, Pages: 526-534, ISSN: 2213-8587
BackgroundIndian 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.MethodsWe 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.Findings1608 (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 baselin
Mostafavi N, Vlaanderen J, Chadeau-Hyam M, et al., 2015, Inflammatory markers in relation to long-term air pollution, Environment International, Vol: 81, Pages: 1-7, ISSN: 0160-4120
Long-term exposure to ambient air pollution can lead to chronic health effects such as cancer, cardiovascular and respiratory disease. Systemic inflammation has been hypothesized as a putative biological mechanism contributing to these adverse health effects. We evaluated the effect of long-term exposure to air pollution on blood markers of systemic inflammation.We measured a panel of 28 inflammatory markers in peripheral blood samples from 587 individuals that were biobanked as part of a prospective study. Participants were from Varese and Turin (Italy) and Umea (Sweden). Long-term air pollution estimates of nitrogen oxides (NOx) were available from the European Study of Cohorts for Air Pollution Effects (ESCAPE). Linear mixed models adjusted for potential confounders were applied to assess the association between NOx and the markers of inflammation.Long-term exposure to NOx was associated with decreased levels of interleukin (IL)-2, IL-8, IL-10 and tumor necrosis factor-α in Italy, but not in Sweden. NOx exposure levels were considerably lower in Sweden than in Italy (Sweden: median (5th, 95th percentiles) 6.65 μg/m3 (4.8, 19.7); Italy: median (5th, 95th percentiles) 94.2 μg/m3 (7.8, 124.5)). Combining data from Italy and Sweden we only observed a significant association between long-term exposure to NOx and decreased levels of circulating IL-8.We observed some indication for perturbations in the inflammatory markers due to long-term exposure to NOx. Effects were stronger in Italy than in Sweden, potentially reflecting the difference in air pollution levels between the two cohorts.
Guida F, Sandanger TM, Castagne R, et al., 2015, Dynamics of smoking-induced genome-wide methylation changes with time since smoking cessation, Human Molecular Genetics, Vol: 24, Pages: 2349-2359, ISSN: 0964-6906
Several studies have recently identified strong epigenetic signals related to tobacco smoking. However, an aspect that did not receive much attention is the evolution of epigenetic changes with time since smoking cessation. We conducted a series of epigenome-wide association studies to capture the dynamics of smoking-induced epigenetic changes after smoking cessation, using genome-wide methylation profiles obtained from blood samples in 745 women from 2 European populations. Two distinct classes of CpG sites were identified: sites whose methylation reverts to levels typical of never smokers within decades after smoking cessation, and sites remaining differentially methylated, even more than 35 years after smoking cessation. Our results suggest that the dynamics of methylation changes following smoking cessation are driven by a differential and site-specific magnitude of the smoking-induced alterations (with persistent sites being most affected) irrespective of the intensity and duration of smoking. Analyses of the link between methylation and expression levels revealed that methylation predominantly and remotely down-regulates gene expression. Among genes whose expression was associated with our candidate CpG sites, LRRN3 appeared to be particularly interesting as it was one of the few genes whose methylation and expression were directly associated, and the only gene in which both methylation and gene expression were found associated with smoking. Our study highlights persistent epigenetic markers of smoking, which can potentially be detected decades after cessation. Such historical signatures are promising biomarkers to refine individual risk profiling of smoking-induced chronic disease such as lung cancer.
Johnson MR, Behmoaras J, Bottolo L, et al., 2015, Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus, Nature Communications, Vol: 6, ISSN: 2041-1723
Gene-regulatory network analysis is a powerful approach to elucidate the molecular processes and pathways underlying complex disease. Here we employ systems genetics approaches to characterize the genetic regulation of pathophysiological pathways in human temporal lobe epilepsy (TLE). Using surgically acquired hippocampi from 129 TLE patients, we identify a gene-regulatory network genetically associated with epilepsy that contains a specialized, highly expressed transcriptional module encoding proconvulsive cytokines and Toll-like receptor signalling genes. RNA sequencing analysis in a mouse model of TLE using 100 epileptic and 100 control hippocampi shows the proconvulsive module is preserved across-species, specific to the epileptic hippocampus and upregulated in chronic epilepsy. In the TLE patients, we map the trans-acting genetic control of this proconvulsive module to Sestrin 3 (SESN3), and demonstrate that SESN3 positively regulates the module in macrophages, microglia and neurons. Morpholino-mediated Sesn3 knockdown in zebrafish confirms the regulation of the transcriptional module, and attenuates chemically induced behavioural seizures in vivo.
Fages A, Ferrari P, Monni S, et al., 2014, Investigating sources of variability in metabolomic data in the EPIC study: the Principal Component Partial <i>R</i>-square (PC-PR2) method, METABOLOMICS, Vol: 10, Pages: 1074-1083, ISSN: 1573-3882
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Guida F, Campanella G, Sandanger T, et al., 2014, 0220 Identification of short-term, long-term and lifelong DNA methylation markers of exposure to tobacco smoke: evidence from EPIC and NOWAC studies., Occup Environ Med, Vol: 71 Suppl 1, Pages: A29-A30
OBJECTIVES: The aim of our study is to validate and complement recently reported epigenetic biomarkers of exposure to tobacco smoke based on data from two cohorts and to characterise their prospective nature. METHOD: We used case-control data from studies nested in two prospective cohorts: the Italian component of the European Prospective Investigation into Cancer and Nutrition study (N = 620) and the Norwegian Women and Cancer study (N = 382) as a validation dataset. For each of the participant, genome wide methylation profiles were acquired from blood samples collected at enrolment using the Illumina HM450 DNA methylation array. We performed epigenome wide association studies within each dataset to assess the relation between methylation levels and smoking-related variables, controlling for technical variation (batch effects) and confounding factors (including white blood cell composition). RESULTS: We found 8 and 897 CpG sites differentially methylated in former and current smokers, while compared to never smokers, respectively. The 8 candidate markers of former smoking showed a gradual reversion of their methylation levels from those typical of current smokers to those of never smokers. Further analyses using cumulative (over varying time windows) smoking intensities, highlighted three classes of biomarkers: short and long term biomarkers (measuring the effect of smoking in the past 10, and in the past 10 to 30 years respectively), and lifelong biomarkers detected more than 30 years after quitting smoking. CONCLUSIONS: Genome-wide DNA methylation profiles show promising abilities to detect short-term to lifelong biomarkers of tobacco smoke exposure and, more generally, to potentially identify time-varying biomarkers of exposure.
Chadeau-Hyam M, 2014, 0380 Dynamics of exposure and disease progression: the use of compartmental models., Occup Environ Med, Vol: 71 Suppl 1, Pages: A122-A123
OBJECTIVES: Chronic diseases are usually slow-developing condition and their risk may result from both long-term exposure and successive exposure increments, hence calling for models accounting for dynamics of exposure and disease progression. METHOD: Discrete compartmental models are defined by a set of ordered states (compartments) reflecting the health status, and can be fully characterised by the set of transition probabilities between each compartment. When defined at the individual level, each participant contributes to the likelihood of the model at each year from the time of entering the initial stage (e.g. birth) to the moment they reach an absorbing state (e.g. death or clinical onset). Model estimation aims at quantifying the transitions ensuring the best reconstruction of the pathological trajectories in each subject, hence adding to the classification problem (discriminating healthy and diseased subjects) a dynamic component (estimating the time of onset). Individual exposure histories can be summarised through cumulative exposure functions and subsequently plugged into the compartmental framework as parameters of transition probabilities. RESULTS: While these models were initially developed to accommodate data from longitudinal studies, we will illustrate, using lung cancer case control and smoking history data, the validity and utility of such approaches. We will assess the underlying assumptions yielded by this methodological drift and will exemplify the rich statistical inference these approaches are able to provide. CONCLUSIONS: We will finally introduce potential extensions over this framework that include omics biomarkers to model genetically-driven susceptibility and/or to identify the stage (s) at which exposure (s) are more likely to mediate their effects.
Chadeau-Hyam M, Vermeulen RCH, Hebels DGAJ, et al., 2014, Prediagnostic transcriptomic markers of Chronic lymphocytic leukemia reveal perturbations 10 years before diagnosis, Annals of Oncology, Vol: 25, Pages: 1065-1072, ISSN: 0923-7534
BackgroundB-cell lymphomas are a diverse group of hematological neoplasms with differential etiology and clinical trajectories. Increased insights in the etiology and the discovery of prediagnostic markers have the potential to improve the clinical course of these neoplasms.MethodsWe investigated in a prospective study global gene expression in peripheral blood mononuclear cells of 263 incident B-cell lymphoma cases, diagnosed between 1 and 17 years after blood sample collection, and 439 controls, nested within two European cohorts.ResultsOur analyses identified only transcriptomic markers for specific lymphoma subtypes; few markers of multiple myeloma (N = 3), and 745 differentially expressed genes in relation to future risk of chronic lymphocytic leukemia (CLL). The strongest of these associations were consistently found in both cohorts and were related to (B-) cell signaling networks and immune system regulation pathways. CLL markers exhibited very high predictive abilities of disease onset even in cases diagnosed more than 10 years after blood collection.ConclusionsThis is the first investigation on blood cell global gene expression and future risk of B-cell lymphomas. We mainly identified genes in relation to future risk of CLL that are involved in biological pathways, which appear to be mechanistically involved in CLL pathogenesis. Many but not all of the top hits we identified have been reported previously in studies based on tumor tissues, therefore suggesting that a mixture of preclinical and early disease markers can be detected several years before CLL clinical diagnosis.
Stamler J, Brown IJ, Yap IKS, et al., 2013, Dietary and Urinary Metabonomic Factors Possibly Accounting for Higher Blood Pressure of Black Compared With White Americans Results of International Collaborative Study on Macro-/Micronutrients and Blood Pressure, HYPERTENSION, Vol: 62, Pages: 1074-1080, ISSN: 0194-911X
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Kelly RS, Lundh T, Porta M, et al., 2013, Blood Erythrocyte Concentrations of Cadmium and Lead and the Risk of B-Cell Non-Hodgkin's Lymphoma and Multiple Myeloma: A Nested Case-Control Study, PLOS One, Vol: 8, ISSN: 1932-6203
Background: Cadmium (Cd) and lead (Pb) are hypothesised to be risk factors for non-Hodgkin’s lymphoma (NHL), agroup of haematological malignancies with a suspected environmental aetiology. Within the EnviroGenoMarkersstudy we utilised pre-diagnostic erythrocyte concentrations of Cd and Pb to determine whether exposure wasassociated with risk of B-cell NHL and multiple myeloma.Methods: 194 incident cases of B-cell NHL and 76 cases of multiple myeloma diagnosed between 1990 and 2006were identified from two existing cohorts; EPIC-Italy and the Northern Sweden Health and Disease Study. Caseswere matched to healthy controls by centre, age, gender and date of blood collection. Cd and Pb were measured inblood samples provided at recruitment using inductively coupled plasma-mass spectrometry. Logistic regression wasapplied to assess the association with risk. Analyses were stratified by cohort and gender and by subtype wherepossible.Results: There was little evidence of an increased risk of B-cell NHL or multiple myeloma with exposure to Cd (B-cellNHL: OR 1.09 95%CI 0.61, 1.93, MM: OR 1.16 95% CI: 0.40, 3.40 ) or Pb (B-cell NHL: 0.93 95% CI 0.43, 2.02,multiple myeloma: OR 1.63 95%CI 0.45, 5.94) in the total population when comparing the highest to the lowestquartile of exposure. However, gender and cohort specific differences in results were observed. In females the risk ofB-cell NHL was more than doubled in those with a body burden of Cd >1µg/L (OR 2.20 95%CI; 1.04, 4.65).Conclusions: This nested case-control study does not support a consistent positive association between Cd or Pband NHL, but there is some indication of a gender specific effect suggesting further research is warranted.
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