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Chromosomal distribution and DNA methylation trends of the significant age-modified CpG sites. (A) Dot plot showing the chromosomal distribution of age-methylated CpGs (blue dots) and age-demethylated CpGs (red dots) in relation to the Bonferroni-corrected P value. For methylated genes: TTC22 = tetratricopeptide repeat domain 22; NES = nestin; NGEF = neuronal guanidine nucleotide exchange factor; SNED1 = sushi nidogen and EGF-like domains 1; FOXI2 = forkhead box I2; LAG3 = lymphocyte activation gene 3; CRYL1 = crystallin lambda 1; TEPP = testis prostate and placenta expressed; TSC2 = tuberous sclerosis 2; RHBDL3 = rhomboid, veinlet-like 3 (Drosophila); NFIX = nuclear factor I/X; TMC2: transmembrane channel-like 2; SOX10 = SRY-box 10. For demethylated genes: ATOH8 = atonal homolog 8; CLEC3B = C-type lectin domain family 3, member B, NRG2 = neuregulin 2; PTK7 = protein tyrosine kinase 7; ANKRD2 = ankyrin repeat domain 2; JRKL = JRK-like; NOD2 = nucleotide-binding oligomerization domain containing 2; ARID3A = AT-rich interactive domain 3A; ZMYND8 = zinc finger, MYND-type containing 8; TSPO = translocator protein (18 kDa); CLDN2 = claudin 2. An asterisk next to the gene symbol indicates that the age-modified CpG site has similar DNA methylation levels in sorted blood leukocytes of healthy adults. Genes in bold indicate that the annotated CpG site is embedded in an age-modified region. Detailed information on P values is presented in Additional file 1. (B) Time trends in DNA methylation (M value) for age-methylated sites (blue) and age-demethylated sites (red). M values above 1 represent that the site is methylated, and M values below −1 represent that the site is demethylated. A value of 0 is proportional to a beta value of 0.50. Each line represents a CpG site.
Source publication
Age-related changes in DNA methylation occurring in blood leukocytes during early childhood may reflect epigenetic maturation. We hypothesized that some of these changes involve gene networks of critical relevance in leukocyte biology and conducted a prospective study to elucidate the dynamics of DNA methylation. Serial blood samples were collected...
Contexts in source publication
Context 1
... chromosomal distribution of the age-modified CpG sites according to their Bonferroni-corrected P value (p bonf ) is presented in Figure 2A. Genes containing the most sig- nificant age-modified CpG sites in peripheral blood leuko- cytes within 5 years after birth are annotated in the figure (p bonf below 6.5 × 10 −8 (E) Number of age-modified CpG sites that were found homogeneously methylated in seven populations of sorted blood leukocytes, granulocytes and peripheral blood mononuclear cells (PBMCs) from healthy adults as described in [34]. ...
Context 2
... list of age-modified CpG sites with homogeneous methylation in sorted leukocytes is presented in Additional file 1. . The majority of the top significant age-methylated CpG sites were also homoge- neously methylated in sorted peripheral blood leukocytes from healthy adults (showed with an asterisk in Figure 2A). Furthermore, we found that many of the top significant age-modified CpG sites were embedded into age-modified regions (see Figure 2A, Tables 2 and 3). ...
Context 3
... majority of the top significant age-methylated CpG sites were also homoge- neously methylated in sorted peripheral blood leukocytes from healthy adults (showed with an asterisk in Figure 2A). Furthermore, we found that many of the top significant age-modified CpG sites were embedded into age-modified regions (see Figure 2A, Tables 2 and 3). Examples of the time trends for age effects on DNA methylation in methyl- ated and demethylated sites are presented in Figure 2B. ...
Context 4
... we found that many of the top significant age-modified CpG sites were embedded into age-modified regions (see Figure 2A, Tables 2 and 3). Examples of the time trends for age effects on DNA methylation in methyl- ated and demethylated sites are presented in Figure 2B. Overall, the kinetics of the DNA methylation changes over time differed according to each site. ...
Context 5
... the kinetics of the DNA methylation changes over time differed according to each site. Some CpGs were ini- tially unmethylated (M value below −1) and became meth- ylated (M value above 1) while other CpGs had M values above 1 that further increased over time ( Figure 2B). Since the majority of age-modified CpG sites were associ- ated to a known transcript ( Figure 1D) and their location can provide insights on their putative biological relevance, we analysed the genomic distribution of the 794 age- modified CpG sites according to their proximity to a CpG island and other genomic regulatory features like DNAse I hypersensitivity sites (DHSs) and enhancers. ...
Citations
... Out of these 25 CpGs, 7 are located in genes BST2, FKBP5, PRDX5, NWD1, FAM38A and NOD2, which have previously shown high association between DNAm and aging (39)(40)(41)(42), and we have already identified cg16363586 (located in gene BST2) as life expectancy associated site (20). In addition, the CpG site that was identified as mortality-associated in both cohorts with the 27 CpG signature, cg11436113, has been reported as smoking and cancer related (43,44). ...
Background
Epigenetic aging signatures can provide insights into the human aging process. Within the last decade many alternative epigenetic clocks have been described, which are typically based on linear regression analysis of DNA methylation at multiple CG dinucleotides (CpGs). However, this approach assumes that the epigenetic modifications follow either a continuous linear or logarithmic trajectory. In this study, we explored an alternative non-parametric approach using 2D-kernel density estimation (KDE) to determine epigenetic age.
Results
We used Illumina BeadChip profiles of blood samples of various studies, exemplarily selected the 27 CpGs with highest linear correlation with chronological age (R ² > 0.7), and computed KDEs for each of them. The probability profiles for individual KDEs were further integrated by a genetic algorithm to assign an optimal weight to each CpG. Our weighted 2D-kernel density estimation model (WKDE) facilitated age-predictions with similar correlation and precision (R ² = 0.81, median absolute error = 4 years) as other commonly used clocks. Furthermore, our approach provided a variation score, which reflects the inherent variation of age-related epigenetic changes at different CpG sites within a given sample. An increase of the variation score by one unit reduced the mortality risk by 9.2% (95% CI (0.8387, 0.9872), P <0.0160) in the Lothian Birth Cohort 1921 after adjusting for chronological age and sex.
Conclusions
We describe a new method using weighted 2D-kernel density estimation (WKDE) for accurate epigenetic age-predictions and to calculate variation scores, which provide an additional variable to estimate biological age.
... (D) demonstrates the utility of epigenetic asthma biomarkers at different time points. (E) shows the key genes undergoing changes in methylation during development [33][34][35]. ...
... Cord blood generally displays low levels of methylation across the genome [53,54] followed by a rapid increase in early life [34,54], and a gradual loss in later years [2]. CpG sites linked to embryonic developmental genes gain methylation in childhood, while regions related to immune processes lose methylation [33]. For example, genes located in Major Histocompatibility Complex (MHC) classes I and II [33,55]-in particular HLA-B, HLA-C, HLA-DMA, and HLA-DPB1-become demethylated with age. ...
... CpG sites linked to embryonic developmental genes gain methylation in childhood, while regions related to immune processes lose methylation [33]. For example, genes located in Major Histocompatibility Complex (MHC) classes I and II [33,55]-in particular HLA-B, HLA-C, HLA-DMA, and HLA-DPB1-become demethylated with age. MHC I and II play a crucial role in the immune response and have been implicated in asthma and allergic disease ( Figure 2E) [56,57]. ...
DNA methylation (DNAm) is a dynamic, age-dependent epigenetic modification that can be used to study interactions between genetic and environmental factors. Environmental exposures during critical periods of growth and development may alter DNAm patterns, leading to increased susceptibility to diseases such as asthma and allergies. One method to study the role of DNAm is the epigenetic clock—an algorithm that uses DNAm levels at select age-informative Cytosine-phosphate-Guanine (CpG) dinucleotides to predict epigenetic age (EA). The difference between EA and calendar age (CA) is termed epigenetic age acceleration (EAA) and reveals information about the biological capacity of an individual. Associations between EAA and disease susceptibility have been demonstrated for a variety of age-related conditions and, more recently, phenotypes such as asthma and allergic diseases, which often begin in childhood and progress throughout the lifespan. In this review, we explore different epigenetic clocks and how they have been applied, particularly as related to childhood asthma. We delve into how in utero and early life exposures (e.g., smoking, air pollution, maternal BMI) result in methylation changes. Furthermore, we explore the potential for EAA to be used as a biomarker for asthma and allergic diseases and identify areas for further study.
... The authors described age-related methylation in PTGER2 and PTGER4. The methylation in leukocytes and, thus, the possible activity of these genes decreased with age [30]. Despite the fact that the common denominator is age, the current study showed an increase with age, but our analysis was performed in whole blood and not in individual subpopulations of cells. ...
Prostaglandin signaling pathways are closely related to inflammation, but also muscle regeneration and processes associated with frailty and sarcopenia, whereas β-catenin (CTNNB1 gene) as a part of Wnt signaling is also involved in the differentiation of muscle cells and fibrosis. The present study analyzed the association between selected prostaglandin pathway genes and clinical parameters in patients with sarcopenia and frailty syndrome. The present study was conducted on patients with sarcopenia, frailty syndrome, and control older patients (N = 25). Additionally, two healthy controls at the age of 25–30 years (N = 51) and above 50 years old (N = 42) were included. The expression of the PTRGER4, PTGES2 (COX2), PTGS2, and CTNNB1 genes in whole blood was checked by the qPCR method. The serum cytokine levels (IL-10, TNFα, IFN-y, IL-1α, IL-1β) in patients and controls were checked by the Q-Plex Human Cytokine Panel. The results showed a significant effect of age on PTGER4 gene expression (p = 0.01). A negative trend between the appendicular skeletal muscle mass parameter (ASSM) and the expression of PTGER4 has been noted (r = −0.224, p = 0.484). PTGES2 and PTGS2 expressions negatively correlated with creatine phosphokinase (r = −0.71, p = 0.009; r = −0.58, p = 0.047) and positively with the functional mobility test timed up and go scale (TUG) (r = 0.61, p = 0.04; r = 0.63, p = 0.032). In the older control group, a negative association between iron levels and the expression of PTGS2 (r = −0.47, p = 0.017) was observed. A similar tendency was noted in patients with sarcopenia (r = −0.112, p = 0.729). A negative trend between appendicular skeletal muscle mass (ASMM) and PTGER4 seems to confirm the impairment of muscle regeneration associated with sarcopenia. The expression of the studied genes revealed a trend in associations with the clinical picture of muscular dystrophy and weakening patients. Perhaps PTGS2 and PTGES2 is in opposition to the role of the PTGER4 receptor in muscle physiology. Nevertheless, further, including functional studies is needed.
... Therefore, the results presented in this manuscript provide a systematic, comprehensive analysis of the epigenetic dynamics associated with the early postnatal development, the prenatal intrauterine conditioning and the interactions between both processes in a longitudinal fashion. Regarding postnatal development, our results are in line with previous studies that establish the first 5 years of life [22] as the most critical for epigenetic remodelling, especially during the first 3 years [48]. The uncovering of the epigenetic relevance of the first six months of life could lead to new studies that point the importance of earlier lifestyle interventions on adult health, especially at the cardiovascular level. ...
... On the other hand, loci involved in gene regulatory networks of embryonic development concentrate hypermethylation signatures in their promoter regions, consolidating Polycomb-mediated gene repression programmes once developmental processes have concluded [50,51]. These results agree with previous longitudinal studies carried out from birth up to 10 years [22,48]. All in all, early postnatal development is tightly regulated at the epigenetic level according to the direction of the methylation changes. ...
Background
Obesity is a negative chronic metabolic health condition that represents an additional risk for the development of multiple pathologies. Epidemiological studies have shown how maternal obesity or gestational diabetes mellitus during pregnancy constitute serious risk factors in relation to the appearance of cardiometabolic diseases in the offspring. Furthermore, epigenetic remodelling may help explain the molecular mechanisms that underlie these epidemiological findings. Thus, in this study we explored the DNA methylation landscape of children born to mothers with obesity and gestational diabetes during their first year of life.
Methods
We used Illumina Infinium MethylationEPIC BeadChip arrays to profile more than 770,000 genome-wide CpG sites in blood samples from a paediatric longitudinal cohort consisting of 26 children born to mothers who suffered from obesity or obesity with gestational diabetes mellitus during pregnancy and 13 healthy controls (measurements taken at 0, 6 and 12 month; total N = 90). We carried out cross-sectional and longitudinal analyses to derive DNA methylation alterations associated with developmental and pathology-related epigenomics.
Results
We identified abundant DNA methylation changes during child development from birth to 6 months and, to a lesser extent, up to 12 months of age. Using cross-sectional analyses, we discovered DNA methylation biomarkers maintained across the first year of life that could discriminate children born to mothers who suffered from obesity or obesity with gestational diabetes. Importantly, enrichment analyses suggested that these alterations constitute epigenetic signatures that affect genes and pathways involved in the metabolism of fatty acids, postnatal developmental processes and mitochondrial bioenergetics, such as CPT1B, SLC38A4, SLC35F3 and FN3K. Finally, we observed evidence of an interaction between developmental DNA methylation changes and maternal metabolic condition alterations.
Conclusions
Our observations highlight the first six months of development as being the most crucial for epigenetic remodelling. Furthermore, our results support the existence of systemic intrauterine foetal programming linked to obesity and gestational diabetes that affects the childhood methylome beyond birth, which involves alterations related to metabolic pathways, and which may interact with ordinary postnatal development programmes.
... Age of patients is another factor that strongly affects levels of methylation [32,33]. Sharp et al. also mentioned "Age-related methylation", in which the level of methylation can change over time [25]. ...
Orofacial clefts are among the most common craniofacial anomalies with multifactorial etiologies, including genetics and environments. DNA methylation, one of the most acknowledged mechanisms of epigenetics, is involved in the development of orofacial clefts. DNA methylation has been examined in patients with non-syndromic cleft lip with cleft palate (nsCL/P) from multiple specimens, including blood, saliva, lip, and palate, as well as experimental studies in mice. The results can be reported in two different trends: hypomethylation and hypermethylation. Both hypomethylation and hypermethylation can potentially increase the risk of nsCL/P depending on the types of specimens and the specific regions on each gene and chromosome. This is the most up-to-date review, intending to summarize evidence of the alterations of DNA methylation in association with the occurrence of orofacial clefts. To make things straightforward to understand, we have systematically categorized the data into four main groups: human blood, human tissues, animal models, and the factors associated with DNA methylation. With this review, we are moving closer to the core of DNA methylation associated with nsCL/P development; we hope this is the initial step to find a genetic tool for early detection and prevention of the occurrence of nsCL/P.
... This may be due to the existence of sensitive periods in early life-limited windows of receptivity during development when an individual is particularly responsive to certain exposures, such as stressful experiences, potentially resulting in adaptations that may be present through other life stages [1,58]. Ideal studies would obtain longitudinal biological samples across the life course and consider what age or ages are most appropriate to answer the research question [90][91][92]. Recent research in childhood trauma similarly strongly encourages only drawing conclusions from longitudinal research [83]. ...
Purpose of Review
There is a great deal of interest regarding the biological embedding of childhood trauma and social exposures through epigenetic mechanisms, including DNA methylation (DNAm), but a comprehensive understanding has been hindered by issues of limited reproducibility between studies. This review presents a summary of the literature on childhood trauma and DNAm, highlights issues in the field, and proposes some potential solutions.
Recent Findings
Investigations of the associations between DNAm and childhood trauma are commonly performed using candidate gene approaches, specifically involving genes related to neurological and stress pathways. Childhood trauma is defined in a wide range of ways in several societal contexts. However, although variations in DNAm are frequently found in stress-related genes, unsupervised epigenome-wide association studies (EWAS) have shown limited reproducibility both between studies and in relating these changes to exposures.
Summary
The reproducibility of childhood trauma DNAm studies, and the field of social epigenetics in general, may be improved by increasing sample sizes, standardizing variables, making use of effect size thresholds, collecting longitudinal and intervention samples, appropriately accounting for known confounding factors, and applying causal analysis wherever possible, such as “two-step epigenetic Mendelian randomization.”
... 8,9 Understanding immune maturation during these life stages is essential since studies in animal models and human populations have shown an "immunological window of opportunity", 10,11 a period early in life where the immune system is particularly amenable to environmental stimuli and genome-wide demethylation of critical immune genes occur. 12,13 Many immunological or immune-related diseases such as type I diabetes, 14 asthma, and allergies 11,[15][16][17] have been linked to early-life environmental exposures. ...
... To [18][19][20] particularly to food allergens early in life. 21,28,29 This study revealed that even though all children showed similar immune cell composition at birth, they could be separated into two Population frequencies are shown as a fraction of all cells different from peripheral blood even after the first days of life, 12,13 and this study highlights that the most drastic changes toward a maternal phenotype occur at some point between birth and two years of age, for all cell types except monocytes ( Figure 3). ...
... 8,9 Our DNA methylation studies in human samples at 3, 6, and 12 months after birth also support that during the time window between 0 and two years occur dramatic changes in immune genes that find a plateau between 36 and 60 months. 12 Overall, supporting the observations about the changes in cell composition detected in this study but further studies are needed to analyze the dynamics of immune cell composition during infancy in more detail. ...
Background
Changes in immune cell composition during the immunological window within the first years after birth are not fully understood, especially the effect that different lifestyles might have on immune cell functionality.
Methods
Peripheral blood mononuclear cells from mothers and their children at birth and at two anvd five years were analyzed by mass cytometry. Immune cell composition and functionality was analyzed according to family lifestyle (anthroposophic and non‐anthroposophic).
Results
We found no significant differences in the proportions of major immune lineages between anthroposophic and non‐anthroposophic children at each time point, but there were clear changes over time in the proportions of mononuclear leukocytes, especially in B‐cells and T lymphocytes. Phenotypic distances between cord blood and maternal blood were high at birth but decreased sharply the first two years, indicating strong phenotypic convergence with maternal cells. We found that children exhibited similar stimulation responses at birth, but subsequently segregated into two discrete functional trajectories. Trajectory 1 was associated with a decrease in tumor necrosis factor alpha (TNFa) production by CD4⁺ T‐ and NK‐cells, while Trajectory 2 depicted an increase in the production of IL‐2 and interferon gamma (INFg) by T‐cells. In both trajectories, there was an increase in IL‐17A production by T‐cells resulting in prominent differences at five years of age.
Conclusions
This exploratory study suggests that leukocyte frequencies and cell phenotypes change with age in the same way across all children, while functional development follows one of two discrete trajectories that largely segregate by family lifestyle, supporting the hypothesis that early environmental exposures imprint immune cell function which may contribute to IgE sensitization. Our results also support that the first two years are critical for the environmental exposures to imprint the immune cells. Further studies with larger sample sizes are required to validate our findings.
... There is increasing evidence demonstrating a key role of epigenetics in regulation of human immunity in health and disease [16,17]. Consistent with this, DNA methylation changes during early childhood have been observed in genes implicated in inflammatory processes, encoded histone modifiers and chromatin remodeling factors [18]. However, the effects of these changes on the immune system are unknown. ...
... Little is known about the function of PRRT1 although aberrant methylation of this gene has been related to neurodevelopmental disorders [24] and to hepatic tumorigenesis [25]. Furthermore, we observed a total of 118 CpGs that were previously reported to be altered between 3 and 60 months in blood leukocytes [18]. In agreement with this previous work, we observed 57 CpGs exhibiting an increase in methylation between 12 and 24 months of age, and 60 CpGs showing a decreased methylation with age [18]. ...
... Furthermore, we observed a total of 118 CpGs that were previously reported to be altered between 3 and 60 months in blood leukocytes [18]. In agreement with this previous work, we observed 57 CpGs exhibiting an increase in methylation between 12 and 24 months of age, and 60 CpGs showing a decreased methylation with age [18]. ...
Background
Pneumococcal infections are a major cause of morbidity and mortality in young children and immaturity of the immune system partly underlies poor vaccine responses seen in the young. Emerging evidence suggests a key role for epigenetics in the maturation and regulation of the immune system in health and disease. The study aimed to investigate epigenetic changes in early life and to understand the relationship between the epigenome and antigen-specific antibody responses to pneumococcal vaccination.
Methods
The epigenetic profiles from 24 healthy children were analyzed at 12 months prior to a booster dose of the 13-valent pneumococcal conjugate vaccine (PCV-13), and at 24 months of age, using the Illumina Methylation 450 K assay and assessed for differences over time and between high and low vaccine responders.
Results
Our analysis revealed 721 significantly differentially methylated positions between 12 and 24 months (FDR < 0.01), with significant enrichment in pathways involved in the regulation of cell–cell adhesion and T cell activation. Comparing high and low vaccine responders, we identified differentially methylated CpG sites ( P value < 0.01) associated with HLA-DPB1 and IL6 .
Conclusion
These data imply that epigenetic changes that occur during early childhood may be associated with antigen-specific antibody responses to pneumococcal vaccines.
... These studies follow groups of individuals over months, years or decades measuring methylation, and if possible, phenotype, at multiple timepoints. The commonest form of longitudinal studies in the EWAS literature are natural history studies, which track methylation trajectories from birth in healthy individuals [19][20][21][22][23][24]. However, it is harder to establish longitudinal Fig. 3 A standard EWAS workflow using Minfi or ChAMP packages. ...
... Longitudinal studies in natural history cohorts demonstrate the dynamic nature of DNA methylation throughout the lifespan, particularly in the early years of life. During the first five years of life, the methylome undergoes drastic remodelling with a tendency towards global hypermethylation [19][20][21][22][23][24]. Methylation changes predominantly occur on autosomal chromosomes [19][20][21][22][23], with hypermethylation in CpG dense regions, including gene promoters, intragenic regions and transcription start sites [20][21][22][23]. ...
... During the first five years of life, the methylome undergoes drastic remodelling with a tendency towards global hypermethylation [19][20][21][22][23][24]. Methylation changes predominantly occur on autosomal chromosomes [19][20][21][22][23], with hypermethylation in CpG dense regions, including gene promoters, intragenic regions and transcription start sites [20][21][22][23]. Hypermethylated genes are overrepresented in developmental functions such as tissue morphogenesis, haematological system development, the effector immune response, neuronal-related functions and cell-cell signalling [21][22][23]. ...
The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.
... However, studies evaluating the persistence of these changes into childhood are scarce (Vaiserman, 2015). Assessing the persistence of these epigenetic modifications is critical as DNAm is a dynamic process that can drift with age (Acevedo et al., 2015). Work by Cardenas et al. in the US-based Project Viva study previously evaluated the persistence of these changes in 321 cord blood samples followed-up in blood samples taken at 10 years of age, finding that higher DNAm levels of the PON1 region were associated with lower cognitive test scores in early childhood for both sexes (Cardenas et al., 2017b). ...
Mercury (Hg) is a ubiquitous heavy metal that originates from both natural and anthropogenic sources and is transformed in the environment to its most toxicant form, methylmercury (MeHg). Recent studies suggest that MeHg exposure can alter epigenetic modifications during embryogenesis. In this study, we examined associations between prenatal MeHg exposure and levels of cord blood DNA methylation (DNAm) by meta-analysis in up to seven independent studies (n = 1462) as well as persistence of those relationships in blood from 7 to 8 year-old children (n = 794). In cord blood, we found limited evidence of differential DNAm at cg24184221 in MED31 (β = 2.28 × 10⁻⁴, p-value = 5.87 × 10⁻⁵) in relation to prenatal MeHg exposure. In child blood, we identified differential DNAm at cg15288800 (β = 0.004, p-value = 4.97 × 10⁻⁵), also located in MED31. This repeated link to MED31, a gene involved in lipid metabolism and RNA Polymerase II transcription function, may suggest a DNAm perturbation related to MeHg exposure that persists into early childhood. Further, we found evidence for association between prenatal MeHg exposure and child blood DNAm levels at two additional CpGs: cg12204245 (β = 0.002, p-value = 4.81 × 10⁻⁷) in GRK1 and cg02212000 (β = −0.001, p-value = 8.13 × 10⁻⁷) in GGH. Prenatal MeHg exposure was associated with DNAm modifications that may influence health outcomes, such as cognitive or anthropometric development, in different populations.
