Background Lower socioeconomic position (SEP) has consistently been associated with poorer health. Chronic inflammation has been proposed as having a prominent role in the construction of social inequalities in health. Disentangling the effects of social disadvantage along the life course on inflammation is key in elucidating biological mechanisms underlying socioeconomic disparities. In this study we investigate how life course socioeconomic conditions influence omics measures of inflammation at different molecular level traits from a subset of 173 Italian participants of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.
Methods We used genome-wide methylation and transcriptional profiles obtained from blood samples from 178 Italian participants of the EPIC cohort. Starting from 824 genes involved in human inflammatory responses and corresponding to 11 502 CpG sites, we first identified 61 potential cis acting CpG loci whose degree of methylation was associated with gene expression (eMS) at a Bonferonni correction, out of which 78.7% were inversely associated with gene expression in cis . We further investigate the relationships between indicators of SEP at 3 life stages through father’s occupation, education and highest household occupation and the 61 cis eMS, involved in inflammation and functionnally relevant, separately and combined through an inflammatory methylome score. We finally investigated life course effects of early-life SEP experiences by sequentially controlling for time-ordered SEP.
Results Our results consistently show that participants with a less advantaged SEP in young adulthood or in adulthood exhibit, later in life, a lower inflammatory methylome score (β=-0.0075, P-value=0.0067, β=-0.0076, P-value=0.0073 for educational level and highest household occupational position respectively), hence suggesting an overall increased level of expression for the corresponding inflammatory-related genes. Adjusting for either behavioural factors (smoking status, alcohol consumption and physical activity) and bmi, or all of them together only marginally affected our results: effect size estimates showed consistent signs, and associations reach statistical significance (P<0.05) for both participant’s education and highest household occupational position. Adopting a life course approach weakened these associations suggesting a common pathways between young and later in life SEP. Sensitivity analyses indicated that our findings were not affected by the way the inflammatory methylome score was calculated.
Conclusion Our results support the hypothesis that social inequalities impacts, independently from behavioural factors, adult physiology through inflammation and can be observed at the DNA methylation level. Understanding biological mechanisms by which social environment influences the inflammatory system has important implications in treatment and especially in prevention, by potentially identifying modifiable factors in the environment that affect physiological health.
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