The first 2018 epigenetic clock human study was from Finland:
“We evaluated the association between maternal antenatal depression and a novel biomarker of aging at birth, namely epigenetic gestational age (GA) based on fetal cord blood methylation data. We also examined whether this biomarker prospectively predicts and mediates maternal effects on early childhood psychiatric problems.
Maternal history of depression diagnosed before pregnancy and greater antenatal depressive symptoms were associated with child’s lower epigenetic GA. Child’s lower epigenetic GA, in turn, prospectively predicted total and internalizing problems and partially mediated the effects of maternal antenatal depression on internalizing problems in boys.”
Listening to a podcast by one of the coauthors, although the researchers’ stated intent was to determine the etiology of the findings, I didn’t hear any efforts to study the parents in sufficient detail to be able to detect possible intergenerational and transgenerational epigenetic inheritance causes and effects. There were the usual “associated with” and “it could be this, it could be that” hedges, which were also indicators of the limited methods employed toward the study’s limited design.
Why was an opportunity missed to advance human research in this area? Are researchers satisfied with non-causal individual differences non-explanations instead of making efforts in areas that may produce etiological findings?
https://www.jaacap.org/article/S0890-8567(18)30107-2/pdf “The Epigenetic Clock at Birth: Associations With Maternal Antenatal Depression and Child Psychiatric Problems” (not freely available)
The second 2018 epigenetic clock human study was from Alabama:
“We estimated measures of epigenetic age acceleration in 830 Caucasian participants from the Genetics Of Lipid Lowering Drugs and diet Network (GOLDN) considering two epigenetic age calculations.
Both DNA methylation age estimates were highly correlated with chronological age. We found that the Horvath and Hannum measures of epigenetic age acceleration were moderately correlated.
The Horvath age acceleration measure exhibited marginal associations with increased postprandial [after eating a meal] HDL [high-density lipoprotein], increased postprandial total cholesterol, and decreased soluble interleukin 2 receptor subunit alpha (IL2sRα). The Hannum measure of epigenetic age acceleration was inversely associated with fasting HDL and positively associated with postprandial TG [triglyceride], interleukin-6 (IL-6), C-reactive protein (CRP), and tumor necrosis factor alpha (TNFα).
Overall, the observed effect sizes were small.“
https://clinicalepigeneticsjournal.biomedcentral.com/track/pdf/10.1186/s13148-018-0481-4 “Metabolic and inflammatory biomarkers are associated with epigenetic aging acceleration estimates in the GOLDN study”
The third 2018 epigenetic clock human study was a meta-analysis of cohorts from the UK, Italy, Sweden, and Scotland:
“The trajectories of Δage showed a declining trend in almost all of the cohorts with adult sample collections. This indicates that epigenetic age increases at a slower rate than chronological age, especially in the oldest population.
Some of the effect is likely driven by survival bias, where healthy individuals are those maintained within a longitudinal study, although other factors like underlying training population for the respective clocks may also have influenced this trend. It may also be possible that there is a ceiling effect for Δage whereby epigenetic clock estimates plateau.”
https://academic.oup.com/biomedgerontology/advance-article/doi/10.1093/gerona/gly060/4944478 “Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data”