Low socioeconomic status and unhealthy lifestyle habits are associated with premature occurrence of stochastic epigenetic mutations: A meta-analysis within the LIFEPATH project

Abstract

Introduction Low socioeconomic status (SES) is associated with earlier onset of age-related chronic conditions and reduced life expectancy. Epigenetic variability by SES is one of the proposed molecular mechanisms mediating this association. In a recent study, we found that low SES, in both childhood and adulthood is associated with accelerated epigenetic ageing, independent from other risk factors for non-communicable diseases, and that the effect may be partially reversible. DNA methylation is gradually deregulated during ageing by errors in methylation maintenance, a process referred to as epigenetic drift. The number of stochastic epigenetic mutations (SEMs) increases exponentially with age, most likely because of an accumulation of exposure-related damage. Epigenetic deregulation may play a role in the development of age-related diseases. This study, within the LIFEPATH project, aims to disentangle the biomolecular mechanisms mediating health inequalities by SES. We hypothesized that low education level, a marker of low socioeconomic status, and unhealthy lifestyle habits are associated with an acceleration of the occurrence of SEMs and, as a consequence, with an increased risk of age-related diseases. Methods SEMs are defined as extreme outliers, exceeding three times interquartile ranges the first quartile (lower than Q1 − 3 × IQR) or the third quartile higher than (Q3 + 3 × IQR), in the distribution of DNA methylation values for a CpG across samples. We conducted a meta-analysis including thirteen cohorts with more than 15,000 individuals to investigate the association of low SES, smoking, obesity, high alcohol intake, and low physical activity with the total number of SEMs. Additionally, in three prospective case-control studies nested in cohorts, we investigated whether the total number of SEMs is associated with higher risk of different cancers. Finally, we examined whether SEMs are randomly distributed across the genome, or are enriched in functional genomic regions. Results We found that low SES, smoking, obesity, high alcohol intake, and low physical activity modulate the association of the total number of SEMs with ageing. The effect of risk factors is more pronounced at older ages, supporting the hypothesis of an accumulation of SEMs as a biomarker of accumulation of exposure-related genomic damage. In nested case-control studies, a higher number of SEMs was associated with higher risk of lung and breast cancer, suggesting accumulation of SEMs belongs to the causal pathway linking low SES and unhealthy lifestyle with age-related diseases and longevity. Enrichment analyses revealed that the genomic distribution of SEMs is highly non-random, as they are enriched in transcription factor binding sites (TFBS). The most significantly enriched TF is a member of the Polycomb Repressive Complex 2 (PRC2), EZH2, a crucial regulatory element in cancer and other age-related diseases like mental disorders. Conclusions We found that low SES and unhealthy lifestyle habits are associated with premature accumulation of age-related epigenetic mutations and that DNA methylation dysregulation is associated with the development of cancer and other age-related diseases. We have identified novel biomolecular mechanisms mediating health inequalities, suggesting a crucial role of Polycomb Repressive Complex 2 associated genomic regions.