19 results found
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.
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.
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.
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.
Cordero F, Ferrero G, Polidoro S, et al., 2015, Differentially methylated microRNAs in prediagnostic samples of subjects who developed breast cancer in the European Prospective Investigation into Nutrition and Cancer (EPIC-Italy) cohort, CARCINOGENESIS, Vol: 36, Pages: 1144-1153, ISSN: 0143-3334
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
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
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
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.
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, 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.
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
Chadeau-Hyam M, Tubert-Bitter P, Guihenneuc-Jouyaux C, et al., 2013, Dynamics of the Risk of Smoking-Induced Lung Cancer: A Compartmental Hidden Markov Model for Longitudinal Analysis, Epidemiology, Vol: n/a, ISSN: 1044-3983
Polidoro S, Broccoletti R, Campanella G, et al., 2013, Effects of bisphosphonate treatment on DNA methylation in osteonecrosis of the jaw, MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS, Vol: 757, Pages: 104-113, ISSN: 1383-5718
Chadeau-Hyam M, Campanella G, Jombart T, et al., 2013, Deciphering the complex: Methodological overview of statistical models to derive OMICS-based biomarkers, ENVIRONMENTAL AND MOLECULAR MUTAGENESIS, Vol: 54, Pages: 542-557, ISSN: 0893-6692
Campanella G, Iorio MD, Jasra A, et al., 2013, The TimeMachine for inference on stochastic trees
The simulation of genealogical trees backwards in time, from observations up to the most recent common ancestor (MRCA), is hindered by the fact that, while approaching the root of the tree, coalescent events become rarer, with a corresponding increase in computation time. The recently proposed “Time Machine” tackles this issue by stopping the simulation of the tree before reaching the MRCA and correcting for the induced bias. We present a computationally efficient implementation of this approach that exploits multithreading.
Campanella G, Ribeiro RA, 2011, A framework for dynamic multiple-criteria decision making, DECISION SUPPORT SYSTEMS, Vol: 52, Pages: 52-60, ISSN: 0167-9236
Campanella G, Ribeiro RA, Varela LR, 2011, A Model for B2B Supplier Selection, EUROFUSE Workshop on Fuzzy Methods for Knowledge-Based Systems, Publisher: SPRINGER-VERLAG BERLIN, Pages: 221-+, ISSN: 1867-5662
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