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

Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis

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

Международная трудовая миграция и нелегальная миграция в России

Огляд монографії: Метелев С.Е. Международная трудовая миграция и нелегальная миграция в России. Монография. – М.: Юнити. – 2006. – 175 с

A systematic comparison of linear regression-based statistical methods to assess exposome-health associations

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

Life-course socioeconomic status and DNA methylation of genes regulating inflammation

Background: In humans, low socioeconomic status (SES) across the life course is associated with greater diurnal cortisol production, increased inflammatory activity and higher circulating antibodies for several pathogens, all suggesting a dampened immune response. Recent evidence suggests that DNA methylation of pro-inflammatory genes may be implicated in the biological embedding of the social environment. Methods: The present study examines the association between life-course SES and DNA methylation of candidate genes, selected on the basis of their involvement in SES-related inflammation, in the context of a genome-wide methylation study. Participants were 857 healthy individuals sampled from the EPIC Italy prospective cohort study. Results: Indicators of SES were associated with DNA methylation of genes involved in inflammation. NFATC1, in particular, was consistently found to be less methylated in individuals with low vs high SES, in a dose-dependent manner. IL1A, GPR132 and genes belonging to the MAPK family were also less methylated among individuals with low SES. In addition, associations were found between SES and CXCL2 and PTGS2, but these genes were consistently more methylated among low SES individuals. Conclusions: Our findings support the hypothesis that the social environment leaves an epigenetic signature in cells. Although the functional significance of SES-related DNA methylation is still unclear, we hypothesize that it may link SES to chronic disease ris

Epigenetic signatures of internal migration in Italy.

Observational studies have suggested that the risks of non-communicable diseases in voluntary migrants become similar to those in the host population after one or more generations, supporting the hypothesis that these diseases have a predominantly environmental (rather than inherited) origin. However, no study has been conducted thus far to identify alterations at the molecular level that might mediate these changes in disease risk after migration

Effects of exposure to water disinfection by-products in a swimming pool: A metabolome-wide association study

BACKGROUND: Exposure to disinfection by-products (DBPs) in drinking water and chlorinated swimming pools are associated with adverse health outcomes, but biological mechanisms remain poorly understood. OBJECTIVES: Evaluate short-term changes in metabolic profiles in response to DBP exposure while swimming in a chlorinated pool. MATERIALS AND METHODS: The PISCINA-II study (EXPOsOMICS project) includes 60 volunteers swimming 40min 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 2h 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. RESULTS: Exposure 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. CONCLUSION: Our 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