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Contains fulltext : 219496.pdf (Publisher’s version ) (Closed access) DNA methylation is the most studied modification in human population epigenetics. Its information content can be explored in 2 principal ways - epigenome-wide association studies and epigenetic age. The latter likely reflects cellular/biological age and works with impressive accuracy across most tissues. In adults, it associates with various environments and health. However, current epigenetic clocks are not very accurate in the pediatric age range perhaps because DNA methylation changes much faster in children. Addressing this crucial gap, we created a precise tool to estimate DNA methylation age specific to pediatric buccal epithelial cells. This tool has the potential to become the standard reference for epigenetic studies broadly relevant to child development across the spectrum from health to disease.The development of biological markers of aging has primarily focused on adult samples. Epigenetic clocks are a promising tool for measuring biological age that show impressive accuracy across most tissues and age ranges. In adults, deviations from the DNA methylation (DNAm) age prediction are correlated with several age-related phenotypes, such as mortality and frailty. In children, however, fewer such associations have been made, possibly because DNAm changes are more dynamic in pediatric populations as compared to adults. To address this gap, we aimed to develop a highly accurate, noninvasive, biological measure of age specific to pediatric samples using buccal epithelial cell DNAm. We gathered 1,721 genome-wide DNAm profiles from 11 different cohorts of typically developing individuals aged 0 to 20 y old. Elastic net penalized regression was used to select 94 CpG sites from a training dataset (n = 1,032), with performance assessed in a separate test dataset (n = 689). DNAm at these 94 CpG sites was highly predictive of age in the test cohort (median absolute error = 0.35 y). The Pediatric-Buccal-Epigenetic (PedBE) clock was characterized in additional cohorts, showcasing the accuracy in longitudinal data, the performance in nonbuccal tissues and adult age ranges, and the association with obstetric outcomes. The PedBE tool for measuring biological age in children might help in understanding the environmental and contextual factors that shape the DNA methylome during child development, and how it, in turn, might relate to child health and disease. 7 p.

ObjectiveThe first two years of life are a critical period of rapid brain development. Since early neurodevelopment is influenced by prenatal risk factors and genetics, neonatal biomarkers can potentially provide the opportunity to detect early signs of neurodevelopmental delay. We analyzed associations between DNA methylation (DNAm) levels from cord blood, neonatal magnetic resonance imaging (MRI) neuroimaging data, and neurodevelopment at two years of age.MethodsNeurodevelopment was assessed in 161 children from the South African Drakenstein Child Health Study at two years of age using the Bayley Scales of Infant and Toddler Development III. We performed an epigenome-wide association study of neurodevelopmental delay using DNAm levels from cord blood. A mediation analysis was conducted in 51 children to analyze if associations between differential DNAm and neurodevelopmental delay were mediated by altered neonatal brain volumes.ResultsWe found epigenome-wide significant associations between differential DNAm at the SPTBN4 locus (cg26971411, p-value=3.10×10−08), an intergenic region on chromosome 11 (cg00490349, p-value=2.41×10−08) and a differentially methylated region on chromosome 1 (FDR p-value for the region=9.06×10−05) and severe neurodevelopmental delay. While these associations were not mediated by neonatal brain volume, neonatal caudate volumes were independently associated with neurodevelopmental delay, particularly in language (p=0.0443) and motor (p=0.0082) domains.ConclusionDifferential DNAm levels from cord blood and increased neonatal caudate volumes were independently associated with severe neurodevelopmental delay at two years of age. These findings suggest that neurobiological signals for severe developmental delay may be detectable in very early life with implications for identification and intervention design.

BackgroundMutations and multiplications in the gene encoding for alpha-synuclein are associated with Parkinson’s disease (PD). However, not all individuals with alpha-synuclein variants develop PD, suggesting that additional factors are involved. We hypothesized that increased alpha-synuclein might alter epigenetic regulation of PD pathways.ObjectivesTo identify genome-wide DNA methylation and hydroxymethylation changes induced by overexpression of two alpha-synuclein variants in human dopaminergic neurons, and to relate these to the corresponding transcriptome.MethodsWe assessed DNA methylation and hydroxymethylation at >850,000 CpGs using the EPIC BeadChip in LUHMES cells differentiated to dopaminergic neurons. Control LUHMES neurons, LUHMES neurons overexpressing wild type alpha-synuclein, and LUHMES neurons overexpressing A30P alpha-synuclein were compared. We used SMITE network analysis to identify functionally related genes with altered DNA methylation, DNA hydroxymethylation, and/or gene expression, incorporating LUHMES H3K4me1 ChIP-seq to delineate enhancers in addition to the default promoter and gene body regions.ResultsUsing stringent statistical thresholds, we found that increased expression of wild type or A30P mutant alpha-synuclein induced DNA methylation changes at thousands of CpGs and DNA hydroxymethylation changes at hundreds of CpGs. Differentially methylated sites in both genotypes were enriched for several processes including movement-associated pathways and glutamate signaling. For glutamate and other signaling pathways (i.e. PDGF, insulin), this differential DNA methylation was also associated with transcriptional changes.ConclusionsOur results indicated that alpha-synuclein altered the DNA methylome of dopaminergic neurons, influencing regulation of pathways involved in development, signaling, and metabolism. This supports a role for alpha-synuclein in the epigenetic etiology of PD.

Developmental environments influence individuals' long-term health trajectories, and there is increasing emphasis on understanding the biological pathways through which this occurs. Epigenetic aging evaluates DNA methylation at a suite of distinct CpG sites in the genome, and epigenetic age acceleration (EAA) is linked to heightened chronic morbidity and mortality risks in adults. Consequently, EAA provides insights on trajectories of biological aging, which early life experiences may help shape. However, few studies have measured correlates of children's epigenetic aging, especially outside of the U.S. and Europe. In particular, little is known about how children's growth and development relate to EAA in ecologies in which energetic and pathogenic stressors are commonplace. We studied EAA from dried blood spots among Bondongo children (n = 54) residing in a small-scale, fisher-farmer society in a remote region of the Republic of the Congo. Here, infectious disease burdens and their resultant energy demands are high. Children who were heavier for height or taller for age, respectively, exhibited greater EAA, including intrinsic EAA, which is considered to measure EAA internal to cells. Furthermore, we found that children in families with more conflict between parents had greater intrinsic EAA. These results suggest that in contexts in which limited energy must be allocated to competing demands, more investment in growth may coincide with greater EAA, which parallels findings in European children who do not face similar energetic constraints. Our findings also indicate that associations between adverse family environments and greater intrinsic EAA were nonetheless observable but only after adjustment for covariates relevant to the energetically and immunologically demanding nature of the local ecology.

Social anxiety disorder (SAD) is a psychiatric disorder characterized by extensive fear in social situations. Multiple genetic and environmental factors are known to contribute to its pathogenesis. One of the main environmental risk factors is early life adversity (ELA). Evidence is emerging that epigenetic mechanisms such as DNA methylation might play an important role in the biological mechanisms underlying SAD and ELA. To investigate the relationship between ELA, DNA methylation, and SAD, we performed an epigenome-wide association study for SAD and ELA examining DNA from whole blood of a cohort of 143 individuals using DNA methylation arrays. We identified two differentially methylated regions (DMRs) associated with SAD located within the genes SLC43A2 and TNXB. As this was the first epigenome-wide association study for SAD, it is worth noting that both genes have previously been associated with panic disorder. Further, we identified two DMRs associated with ELA within the SLC17A3 promoter region and the SIAH3 gene and several DMRs that were associated with the interaction of SAD and ELA. Of these, the regions within C2CD2L and MRPL28 showed the largest difference in DNA methylation. Lastly, we found that two DMRs were associated with both the severity of social anxiety and ELA, however, neither of them was found to mediate the contribution of ELA to SAD later in life. Future studies are needed to replicate our findings in independent cohorts and to investigate the biological pathways underlying these effects.

Introduction Indoor air pollution and maternal smoking during pregnancy are associated with respiratory symptoms in infants, but little is known about the direct association with lung function or interactions with genetic risk factors. We examined associations of exposure to indoor particulate matter with a 50% cut-off aerodynamic diameter of 10 µm (PM10) and maternal smoking with infant lung function and the role of gene–environment interactions. Methods Data from the Drakenstein Child Health Study, a South African birth cohort, were analysed (n=270). Lung function was measured at 6 weeks and 1 year of age, and lower respiratory tract infection episodes were documented. We measured pre- and postnatal PM10 exposures using devices placed in homes, and prenatal tobacco smoke exposure using maternal urine cotinine levels. Genetic risk scores determined from associations with childhood-onset asthma in the UK Biobank were used to investigate effect modifications. Results Pre- and postnatal exposure to PM10 as well as maternal smoking during pregnancy were associated with reduced lung function at 6 weeks and 1 year as well as with lower respiratory tract infection in the first year. Due to a significant interaction between the genetic risk score and prenatal exposure to PM10, infants carrying more asthma-related risk alleles were more susceptible to PM10-associated reduced lung function (pinteraction=0.007). This interaction was stronger in infants with Black African ancestry (pinteraction=0.001) and nonexistent in children with mixed ancestry (pinteraction=0.876). Conclusions PM10 and maternal smoking exposures were associated with reduced lung function, with a higher susceptibility for infants with an adverse genetic predisposition for asthma that also depended on the infant's ancestry., Our findings from a South African birth cohort study show an association of indoor air pollution with reduced lung function at 6 weeks and 1 year of age, with a higher susceptibility in children with a genetic predisposition for asthma http://bit.ly/2NpkGRr

Background: The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required. Methods: DNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array. Results: Using monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods (r > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44–3.10 years across preprocessing methods. Conclusions: Here, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms.