Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles

Abstract

Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins’ exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.

Multi-omic associations of epigenetic age acceleration are heterogeneously shaped by genetic and environmental influences

“…A total of 13 binary variables were selected to describe the lifestyle of the twins, and in particular their education, leisure time activities, substance use, and social behavior. These were derived from questionnaires completed at home and at the study visit when blood samples were taken, as was described elsewhere (Drouard et al, 2023a). Eleven of these variables were initially categorical and represented frequencies: playing video games, watching videos, playing an instrument, reading, going out, dancing, taking part in a club, going to a fast food restaurant, going to a bar, drinking alcohol, and having alcohol-induced blackouts.…”

“…We created within-pair, binary lifestyle variables for use in within-pair analyses as well (Drouard et al, 2023a). Briefly, these were coded so that “1” indicated a discordant pair, while “0” indicated a concordant pair.…”

“…Several algorithms have been developed to estimate biological aging from DNA methylation data, including six that we used in the current study: Horvath (Horvath, 2013), Hannum (Hannum et al, 2013), GrimAge (Lu et al, 2019), GrimAge2 (Lu et al, 2022), PhenoAge (Levine et al, 2018) and DunedinPACE (Belsky et al, 2022). The EAA estimates derived from each of these clocks have been widely used in studies targeting on phenotypes such as lifestyle (Drouard et al, 2023a), environmental exposures (de Prado-Bert et al, 2021) and diseases (Lundgren et al, 2022; Yusupov et al, 2023; Joyce et al, 2021; Foster et al, 2023; Carbonneau et al, 2024), all of which have demonstrated adverse health outcomes in individuals with greater EAA. However, studies investigating associations between EAA and multiple omics data remain scarce.…”