Abstract MicroRNAs (miRNAs) are key post-transcriptional regulators that play pivotal roles in diverse physiological and pathological processes. They primarily act by inhibiting protein translation and promoting degradation of messenger RNA (mRNA), thereby inducing post-transcriptional regulatory effects. Most miRNAs can travel through blood, in extracellular vesicles, and between maternal and fetal tissues. When altered miRNAs were present in germ cells, this induces epigenetic inheritance, which influences embryonic development after fertilization. Aberrant miRNA expression is associated with a wide range of human diseases. This review article will summarize current evidence on how miRNA dysregulation contributes to transgenerational effects on reproduction, metabolism, and stress-related phenotypes. This research focuses on the impacts of miRNAs on reproductive impairment, obesity, and stress-related phenotypes, and highlights evidence that these epigenetic changes can persist across multiple generations. Relevant studies were identified mainly through PubMed database using “miRNA” and “transgenerational effect”, with a third keyword according to the topic of interest, including “reproduction”, “hormones”, “spermatogenesis”, “obesity”, “high-fat diet”, “diabetes”, “stress”, and “therapy”. In reproduction, environmental pollutants (including endocrine disruptors) can alter miRNA expression, impairing gonadal development, reducing primordial germ cells, inducing granulosa cell apoptosis, and disrupting sex hormone synthesis. miRNA-dependent pathways also affect spermatogenesis, sperm function, and oocyte development. In obesity, miRNAs regulate adipogenesis by modulating signaling pathways and transcription programs that control fat-cell formation. Paternal high-fat diet and gestational diabetes can shift miRNA profiles, raising offspring risk for obesity and metabolic disease. Chronic stress changes miRNA expression in germ cells and embryos, shaping stress reactivity and social behavior in later generations. Prenatal maternal stress is linked to lasting psychiatric vulnerability in offspring, with effects potentially persisting across multiple generations without continued stress. Overall, miRNA dysregulation can impair reproduction, metabolism, and stress responses, and these effects may be transmitted transgenerationally via epigenetic mechanisms.
Abstract Drosophila melanogaster, a widely used model organism in biology, offers a good platform to study the transgenerational effects of environmental toxicants and pharmaceuticals. Offspring phenotypes are not solely shaped by inherited DNA but also by parental environmental exposures. In this review, we explore how juvenile hormone and ecdysone (key endocrine regulators of insect development) serve as molecular entry points for toxicant-induced epigenetic changes. We detailed how mechanisms such as DNA/RNA methylation, histone modification, non-coding RNAs, chromatin remodeling, and RNA methylation, modulate these hormonal pathways and how they can be inherited across generations. The fly’s short lifecycle, conservation with mammalian systems, and minimal ethical constraints make it ideal for screening developmental and transgenerational toxicities. Leveraging this model can help inform drug development, risk assessment, and public health policy.
Abstract Background: Season at birth has been associated with increased risk for psychotic disorders. Epigenetic markers, which can be influenced by environmental exposures, may help to understand the mechanisms of seasonal effects. Aims: To investigate two types of seasonal influences on DNA methylation: season of sampling and season of birth, and to test whether these seasonal effects interact with psychotic disorder risk. Methods: We used two cohorts: a sample of newborns from the Norwegian Mother, Father, and Child Study (MoBa) and a sample of adult participants from the Thematically Organized Psychosis (TOP) sample. The cosinor function from the R package “seasons” was used to identify seasonally methylated positions (SMPs) associated with season of birth and season of sampling. Meta-analyses were performed between results from the MoBa birth cohort, and the TOP healthy adults samples for both season of birth and season of sampling. Interaction analyses between season of birth/season of sampling and psychosis status were conducted in the TOP cohort. Results: In the meta-analysis of healthy controls from our cohorts, we identified six SMPs (IQSEC1, CACNA2D3, TMEM86B, CNOT3, ZNF250, and ARHGEF3) and two SMPs (ZNF250 and SLC6A19) associated with season of sampling and season of birth, respectively. In the interaction analysis, one significant SMP (cg13593913,) was found to be associated with a psychosis diagnosis and season of birth. Conclusion: In our study, we show a potential interaction between season of birth and psychosis diagnosis. These findings highlight the importance of considering the season of birth and season of sampling in epigenetic research.
Abstract Epigenetics is a rapidly expanding field in ageing research. This is partly because changes in DNA methylation are excellent indicators of overall tissue ageing. Here, in a cross-sectional observational study, methylation levels were compared in upper-inner (sun-protected) and lower-outer (sun-exposed) arm skin biopsies of young (21–30 years, n = 24) and older (45–65 years, n = 24) participants of either European or Chinese ancestry. In young sun-protected skin, there were 69 significantly differentially methylated sites (DMSs) between those of Chinese and European ancestry. In a comparison between young and older sun-protected skin (endogenous ageing) there were 3545 pan-ethnic DMSs with a preference for hypermethylation and enrichment at the RNF32, FOXG1, NEFM, and ZIC1 gene loci. For photoageing, 2208 pan-ethnic photoageing DMS were identified with a preference for hypomethylation and enrichment at the HOXB1-3, TWIST1, and TBX20 gene loci. From the photoageing DMSs, 156 CpG sites were selected that consistently differentiated photo-exposed from protected skin even in the young participants. The mean degree of change for these 156 CpG sites was subsequently measured over 5-months in an interventional study on participants’ lower outer-arm skin (n = 42). Participants had regular sun-protection factor (SPF) use on one arm and normal free-living conditions on the contralateral arm. The free-living arm demonstrated greater skin darkening and a significantly larger mean change in methylation compared with the SPF-treated arm. Overall, the results highlight endogenous and photoageing methylation differences in skin and suggest that specific DNA methylation sites can track short-term sun-exposure and its attenuation by SPF use.
Abstract Prenatal exposure to ambient air pollutants has been associated with adverse child health across different populations. In the absence of direct air pollution exposure measures, epigenetic biomarkers can serve as indicators of cumulative exposure. Previously, we developed a methodological pipeline to build a prediction model to distinguish infants highly exposed to air pollutants in utero based on DNA methylation in cord blood samples. Here, we test and refine this pipeline using data from multiple pregnancy cohort sites included in the Environmental influences on Child Health Outcomes (ECHO) Cohort. Levels of prenatal exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and 8-hour maximum ozone (O3) were modeled using geocoded address data and machine learning. DNA methylation was measured using 450K or EPIC arrays. Training and validation sets were created and matched based on exposure level, cohort site, and array type to test the performance of the pipeline prediction model using area under the curve metrics. Among the three exposures, epigenetic-based predictions of PM2.5 and NO2 produced higher area under the curve values (0.64–0.68 and 0.62–0.95, respectively) than those for O3 (0.50–0.75). We identified differences in the performance of the pipeline model across geographical regions, exposure windows, and thresholds used to distinguish “high” and “low” air pollutant exposure. Overall, this pipeline enabled the estimation of air pollution from DNA methylation data, though careful consideration of model inputs is required. Further studies will test the performance of the CpG sites identified by the pipeline to predict child health outcomes.
