Biological marks of early-life socioeconomic experience is detected in the adult inflammatory transcriptome

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Smoking is a major preventable cause of cancers and is increasingly concentrated among the most deprived individuals leading to increasing socioeconomic inequalities in the incidence of cancers linked to smoking. We aimed to estimate the tobacco-attributable cancer burden according to socioeconomic position in France. The analysis was restricted to cancer sites for which tobacco smoking was recognized as a risk factor. Cancer cases by sex, age group and European Deprivation Index (EDI) among people aged 30-74 between 2006 and 2009 were obtained from cancer registries covering ∼20% of the French population. The tobacco-attributable burden of cancer according to EDI was estimated applying the population attributable fraction (PAF) computed with the Peto-Lopez method. The PAF increased from 56% in the least deprived EDI quintile to 70% in the most deprived EDI quintile among men and from 26% to 38% among women. In total, 28% of the excess cancer cases in the four most deprived EDI quintiles in men and 43% in women could be prevented if smoking in these 4 EDI quintiles was similar to that of the least deprived EDI quintile. A substantial smoking-attributable burden of cancer by socioeconomic position was observed in France. The results highlight the need for policies reducing tobacco consumption. More comprehensive interventions integrating the various dimensions of health determinants and proportionate according to socioeconomic position may essentially contribute to the reduction of socioeconomic inequalities in cancer.

Section: Discussionmentioning

confidence: 87%

Tobacco‐attributable burden of cancer according to socioeconomic position in France

Menvielle

Kulhánová

Bryère

et al. 2018

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“…Statistical significance of the effect of the variable of interest was evaluated using the p ‐value of likelihood ratio test comparing the model with and without that variable . We corrected for multiple testing using a permutation‐based approach estimating the per‐test significance level to be applied to control the family wise error rate (FWER) .…”

Section: Methodsmentioning

confidence: 99%

“…As detailed in the Supporting Information, we ran a series of linear mixed models for each disease‐related adduct and each of the 2,670 smoking‐related CpG, setting the methylation level as the variable of interest. These models also accounted for technical variation in the methylation data using a two‐step strategy first estimating, and second removing technically‐induced shifts in measured methylation levels . Results from these analyses were visualized as a bipartite network where edges were selected based on statistical significance of the pairwise associations, correcting for 2,670 tests.…”

Section: Methodsmentioning

confidence: 99%

Agnostic Cys34‐albumin adductomics and DNA methylation: Implication of N‐acetylcysteine in lung carcinogenesis years before diagnosis

Dagnino

Bodinier

Grigoryan

et al. 2019

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Although smoking and oxidative stress are known contributors to lung carcinogenesis, their mechanisms of action remain poorly understood. To shed light into these mechanisms, we applied a novel approach using Cys34-adductomics in a lung cancer nested case-control study (n = 212). Adductomics profiles were integrated with DNA-methylation data at established smoking-related CpG sites measured in the same individuals. Our analysis identified 42 Cys34-albumin adducts, of which 2 were significantly differentially abundant in cases and controls: adduct of N-acetylcysteine (NAC, p = 4.15 × 10 −3 ) and of cysteinyl-glycine (p = 7.89 × 10 −3 ). Blood levels of the former were found associated to the methylation levels at 11 smokingrelated CpG sites. We detect, for the first time in prospective blood samples, and irrespective of time to diagnosis, decreased levels of NAC adduct in lung cancer cases. Altogether, our results highlight the potential role of these adducts in the oxidative stress response contributing to lung carcinogenesis years before diagnosis. *P.V. and M.C.-H. jointly supervised this work Additional Supporting Information may be found in the online version of this article.

“…To adjust results from all PLS analyses for technically induced variation, and as already proposed,25, 26 we inferred de‐noised data from the linear mixed model presented above by subtracting from the observations the estimated random effects.…”

Section: Methodsmentioning

confidence: 99%

Pre‐diagnostic blood immune markers, incidence and progression of B‐cell lymphoma and multiple myeloma: Univariate and functionally informed multivariate analyses

Vermeulen¹,

Hosnijeh²,

Bodinier³

et al. 2018

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Recent prospective studies have shown that dysregulation of the immune system may precede the development of B‐cell lymphomas (BCL) in immunocompetent individuals. However, to date, the studies were restricted to a few immune markers, which were considered separately. Using a nested case–control study within two European prospective cohorts, we measured plasma levels of 28 immune markers in samples collected a median of 6 years before diagnosis (range 2.01–15.97) in 268 incident cases of BCL (including multiple myeloma [MM]) and matched controls. Linear mixed models and partial least square analyses were used to analyze the association between levels of immune marker and the incidence of BCL and its main histological subtypes and to investigate potential biomarkers predictive of the time to diagnosis. Linear mixed model analyses identified associations linking lower levels of fibroblast growth factor‐2 (FGF‐2 p = 7.2 × 10−4) and transforming growth factor alpha (TGF‐α, p = 6.5 × 10−5) and BCL incidence. Analyses stratified by histological subtypes identified inverse associations for MM subtype including FGF‐2 (p = 7.8 × 10−7), TGF‐α (p = 4.08 × 10−5), fractalkine (p = 1.12 × 10−3), monocyte chemotactic protein‐3 (p = 1.36 × 10−4), macrophage inflammatory protein 1‐alpha (p = 4.6 × 10−4) and vascular endothelial growth factor (p = 4.23 × 10−5). Our results also provided marginal support for already reported associations between chemokines and diffuse large BCL (DLBCL) and cytokines and chronic lymphocytic leukemia (CLL). Case‐only analyses showed that Granulocyte‐macrophage colony stimulating factor levels were consistently higher closer to diagnosis, which provides further evidence of its role in tumor progression. In conclusion, our study suggests a role of growth‐factors in the incidence of MM and of chemokine and cytokine regulation in DLBCL and CLL.