Socioeconomic position during pregnancy and DNA methylation signatures at three stages across early life: epigenome-wide association studies in the ALSPAC birth cohort.

BACKGROUND: Socioeconomic experiences are recognized determinants of health, and recent work has shown that social disadvantages in early life may induce sustained biological changes at molecular level that are detectable later in life. However, the dynamics and persistence of biological embedding of socioeconomic position (SEP) remains vastly unexplored. METHODS: Using the data from the ALSPAC birth cohort, we performed epigenome-wide association studies of DNA methylation changes at three life stages (birth, n = 914; childhood at mean age 7.5 years, n = 973; and adolescence at mean age 15.5 years, n = 974), measured using the Illumina HumanMethylation450 Beadchip, in relation to pregnancy SEP indicators (maternal and paternal education and occupation). RESULTS: Across the four early life SEP metrics investigated, only maternal education was associated with methylation levels at birth, and four CpGs mapped to SULF1, GLB1L2 and RPUSD1 genes were identified [false discovery rate (FDR)-corrected P-value <0.05]. No epigenetic signature was found associated with maternal education in child samples, but methylation levels at 20 CpG loci were found significantly associated with maternal education in adolescence. Although no overlap was found between the differentially methylated CpG sites at different ages, we identified two CpG sites at birth and during adolescence which are 219 bp apart in the SULF1 gene that encodes an heparan sulphatase involved in modulation of signalling pathways. Using data from an independent birth cohort, the ENVIRONAGE cohort, we were not able to replicate these findings. CONCLUSIONS: Taken together, our results suggest that parental SEP, and particularly maternal education, may influence the offspring's methylome at birth and adolescence.

Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins.

Importance: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. Objective: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. Design, Setting, and Participants: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). Main Outcomes and Measures: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). Results: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model. Conclusions and Relevance: This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.

Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women.

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 attributable fraction was highest for smoking, followed by physical inactivity then socioeconomic status. Low socioeconomic status was associated with a 2·1-year reduction in life expectancy between ages 40 and 85 years, the corresponding years-of-life-lost were 0·5 years for high alcohol intake, 0·7 years for obesity, 3·9 years for diabetes, 1·6 years for hypertension, 2·4 years for physical inactivity, and 4·8 years for current smoking. INTERPRETATION: Socioeconomic circumstances, in addition to the 25 × 25 factors, should be targeted by local and global health strategies and health risk surveillance to reduce mortality. FUNDING: European Commission, Swiss State Secretariat for Education, Swiss National Science Foundation, the Medical Research Council, NordForsk, Portuguese Foundation for Science and Technology.

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

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.