Search

Accumulating evidence suggests that the intrauterine environment can have an impact on long-term offspring health, so-called ‘fetal programming’. A number of environmental stressors have been studied in humans including maternal nutrition, smoking, substance misuse and mental illness. Although various biological mechanisms are likely to underpin fetal programming effects, there has been a particular focus on epigenetic modifications as potential mediators of observed associations between early environmental exposures and later health outcomes. In this review, we give an overview of evidence supporting a role for epigenetics in fetal programming, highlighting key human and animal studies. We also discuss challenges for research in this area, along with recommendations for future work, and potential therapeutic applications.

Early life exposures are important predictors of adult disease risk. Although the underlying mechanisms are largely unknown, telomere maintenance may be involved. This study investigated the relationship between seasonal differences in parental exposures at time of conception and leukocyte telomere length (LTL) in their offspring. LTL was measured in two cohorts of children aged 2 yrs (N = 487) and 7–9 yrs (N = 218). The association between date of conception and LTL was examined using Fourier regression models, adjusted for age, sex, leukocyte cell composition, and other potential confounders. We observed an effect of season in the older children in all models [likelihood ratio test (LRT) χ²2 = 7.1, p = 0.03; fully adjusted model]. LTL was greatest in children conceived in September (in the rainy season), and smallest in those conceived in March (in the dry season), with an effect size (LTL peak–nadir) of 0.60 z-scores. No effect of season was evident in the younger children (LRT χ²2 = 0.87, p = 0.65). The different results obtained for the two cohorts may reflect a delayed effect of season of conception on postnatal telomere maintenance. Alternatively, they may be explained by unmeasured differences in early life exposures, or the increased telomere attrition rate during infancy.

Epigenome‐wide association studies (EWAS) are designed to characterise population‐level epigenetic differences across the genome and link them to disease. Most commonly, they assess DNA‐methylation status at cytosine‐guanine dinucleotide (CpG) sites, using platforms such as the Illumina 450k array that profile a subset of CpGs genome wide. An important challenge in the context of EWAS is determining a significance threshold for declaring a CpG site as differentially methylated, taking multiple testing into account. We used a permutation method to estimate a significance threshold specifically for the 450k array and a simulation extrapolation approach to estimate a genome‐wide threshold. These methods were applied to five different EWAS datasets derived from a variety of populations and tissue types. We obtained an estimate of α=2.4×10−7 for the 450k array, and a genome‐wide estimate of α=3.6×10−8. We further demonstrate the importance of these results by showing that previously recommended sample sizes for EWAS should be adjusted upwards, requiring samples between ∼10% and ∼20% larger in order to maintain type‐1 errors at the desired level.

Proopiomelanocortin (POMC) is a key mediator of satiety. Epigenetic marks such as DNA methylation may modulate POMC expression and provide a biological link between early life exposures and later phenotype. Animal studies suggest epigenetic marks at POMC are influenced by maternal energy excess and restriction, prenatal stress and Triclosan exposure. Postnatal factors including energy excess, folate, vitamin A, conjugated linoleic acid and leptin may also affect POMC methylation. Recent human studies suggest POMC DNA methylation is influenced by maternal nutrition in early pregnancy and associated with childhood and adult obesity. Studies in children propose a link between POMC DNA methylation and elevated lipids and insulin, independent of body habitus. This review brings together evidence from animal and human studies and suggests that POMC is sensitive to nutritional programming and is associated with a wide range of weight-related and metabolic outcomes.

Background DNA methylation is thought to be an important determinant of human phenotypic variation, but its inherent cell type specificity has impeded progress on this question. At exceptional genomic regions, interindividual variation in DNA methylation occurs systemically. Like genetic variants, systemic interindividual epigenetic variants are stable, can influence phenotype, and can be assessed in any easily biopsiable DNA sample. We describe an unbiased screen for human genomic regions at which interindividual variation in DNA methylation is not tissue-specific. Results For each of 10 donors from the NIH Genotype-Tissue Expression (GTEx) program, CpG methylation is measured by deep whole-genome bisulfite sequencing of genomic DNA from tissues representing the three germ layer lineages: thyroid (endoderm), heart (mesoderm), and brain (ectoderm). We develop a computational algorithm to identify genomic regions at which interindividual variation in DNA methylation is consistent across all three lineages. This approach identifies 9926 correlated regions of systemic interindividual variation (CoRSIVs). These regions, comprising just 0.1% of the human genome, are inter-correlated over long genomic distances, associated with transposable elements and subtelomeric regions, conserved across diverse human ethnic groups, sensitive to periconceptional environment, and associated with genes implicated in a broad range of human disorders and phenotypes. CoRSIV methylation in one tissue can predict expression of associated genes in other tissues. Conclusions In addition to charting a previously unexplored molecular level of human individuality, this atlas of human CoRSIVs provides a resource for future population-based investigations into how interindividual epigenetic variation modulates risk of disease. Electronic supplementary material The online version of this article (10.1186/s13059-019-1708-1) contains supplementary material, which is available to authorized users.

Background\ud The periconceptional period is a time in which environmentally induced changes to the epigenome could have significant consequences for offspring health. Metastable epialleles (MEs) are genomic loci demonstrating interindividual variation in DNA methylation with intraindividual crosstissue correlation, suggesting that methylation states are established in the very early embryo before gastrulation. In our previous Gambian studies, we have shown that ME methylation states in the offspring are predicted by maternal concentrations of certain nutritional biomarkers around the time of conception.\ud \ud Objective\ud We aimed to assess whether the profile of maternal biomarker predictors of offspring methylation differs between rainy and dry seasons in a population of rural Gambians, using a larger set of 50 recently identified MEs.\ud \ud Methods\ud We measured 1-carbon biomarkers in maternal plasma back-extrapolated to conception, and cytosine-phosphate-guanine (CpG) methylation at 50 ME loci in their infants’ blood at a mean age of 3.3 mo (n = 120 mother-child pairs). We tested for interactions between seasonality and effects of biomarker concentrations on mean ME methylation z score. We used backward stepwise linear regression to select the profile of nutritional predictors of methylation in each season and repeated this analysis with biomarker principal components (PCs) to capture biomarker covariation.\ud \ud Results\ud We found preliminary evidence of seasonal differences in biomarker-methylation associations for folate, choline, and homocysteine (interaction P values ≤0.03). Furthermore, in stratified analyses, biomarker predictors of methylation changed between seasons. In the dry season, vitamin B-2 and methionine were positive predictors. In the rainy season, however, choline and vitamin B-6 were positive predictors, and folate and vitamin B-12 were negative predictors. PC1 captured covariation in the folate metabolism cycle and predicted methylation in dry season conceptions. PC2 represented the betaine remethylation pathway and predicted rainy season methylation.\ud \ud Conclusions\ud Underlying nutritional status may modify the association between nutritional biomarkers and methylation, and should be considered in future studies.

The prenatal environment can alter an individual’s developmental trajectory with long-lasting effects on health. Animal models demonstrate that the impact of the early life environment extends to subsequent generations, but there is a paucity of data from human populations on intergenerational transmission of environmentally induced phenotypes. Here we investigated the association of parental exposure to energy and nutrient restriction in utero on their children’s growth in rural Gambia. In a Gambian cohort with infants born between 1972 and 2011, we used multiple regression to test whether parental season of birth predicted offspring birth weight (n = 2097) or length (n = 1172), height-for-age z score (HAZ), weight-for-height z score (WHZ), and weight-for-age z score (WAZ) at 2 yr of age (n = 923). We found that maternal exposure to seasonal energy restriction in utero was associated with reduced offspring birth length (crude:−4.2 mm, P = 0.005; adjusted: −4.0 mm, P = 0.02). In contrast, paternal birth season predicted offspring HAZ at 24 mo (crude: −0.21, P = 0.005; adjusted: −0.22, P = 0.004) but had no discernible impact at birth. Our results indicate that periods of nutritional restriction in a parent’s fetal life can have intergenerational consequences in human populations. Fetal growth appears to be under matriline influence, and postnatal growth appears to be under patriline intergenerational influences.—Eriksen, K. G., Radford, E. J., Silver, M. J., Fulford, A. J. C., Wegmüller, R., Prentice, A. M. Influence of intergenerational in utero parental energy and nutrient restriction on offspring growth in rural Gambia.

Background\ud \ud The consequences of preterm birth are a major public health concern with high rates of ensuing multisystem morbidity, and uncertain biological mechanisms. Common genetic variation may mediate vulnerability to the insult of prematurity and provide opportunities to predict and modify risk.\ud \ud Objective\ud \ud To gain novel biological and therapeutic insights from the integrated analysis of magnetic resonance imaging and genetic data, informed by prior knowledge.\ud \ud Methods\ud \ud We apply our previously validated pathway-based statistical method and a novel network-based method to discover sources of common genetic variation associated with imaging features indicative of structural brain damage.\ud \ud Results\ud \ud Lipid pathways were highly ranked by Pathways Sparse Reduced Rank Regression in a model examining the effect of prematurity, and PPAR (peroxisome proliferator-activated receptor) signaling was the highest ranked pathway once degree of prematurity was accounted for. Within the PPAR pathway, five genes were found by Graph Guided Group Lasso to be highly associated with the phenotype: aquaporin 7 (AQP7), malic enzyme 1, NADP(+)-dependent, cytosolic (ME1), perilipin 1 (PLIN1), solute carrier family 27 (fatty acid transporter), member 1 (SLC27A1), and acetyl-CoA acyltransferase 1 (ACAA1). Expression of four of these (ACAA1, AQP7, ME1, and SLC27A1) is controlled by a common transcription factor, early growth response 4 (EGR-4).\ud \ud Conclusions\ud \ud This suggests an important role for lipid pathways in influencing development of white matter in preterm infants, and in particular a significant role for interindividual genetic variation in PPAR signaling.

The estimated heritability of human BMI is close to 75%, but identified genetic variants explain only a small fraction of interindividual body-weight variation. Inherited epigenetic variants identified in mouse models named “metastable epialleles” could in principle explain this “missing heritability.” We provide evidence that methylation in a variably methylated region (VMR) in the pro-opiomelanocortin gene (POMC), particularly in postmortem human laser-microdissected melanocyte-stimulating hormone (MSH)-positive neurons, is strongly associated with individual BMI. Using cohorts from different ethnic backgrounds, including a Gambian cohort, we found evidence suggesting that methylation of the POMC VMR is established in the early embryo and that offspring methylation correlates with the paternal somatic methylation pattern. Furthermore, it is associated with levels of maternal one-carbon metabolites at conception and stable during postnatal life. Together, these data suggest that the POMC VMR may be a human metastable epiallele that influences body-weight regulation.

Choline is an essential nutrient, and the amount needed in the diet is modulated by several factors. Given geographical differences in dietary choline intake and disparate frequencies of single-nucleotide polymorphisms (SNPs) in choline metabolism genes between ethnic groups, we tested the hypothesis that 3 SNPs that increase dependence on dietary choline would be under negative selection pressure in settings where choline intake is low: choline dehydrogenase (CHDH) rs12676, methylenetetrahydrofolate reductase 1 (MTHFD1) rs2236225, and phosphatidylethanolamine-N-methyltransferase (PEMT) rs12325817. Evidence of negative selection was assessed in 2 populations: one in The Gambia, West Africa, where there is historic evidence of a choline-poor diet, and the other in the United States, with a comparatively choline-rich diet. We used 2 independent methods, and confirmation of our hypothesis was sought via a comparison with SNP data from the Maasai, an East African population with a genetic background similar to that of Gambians but with a traditional diet that is higher in choline. Our results show that frequencies of SNPs known to increase dependence on dietary choline are significantly reduced in the low-choline setting of The Gambia. Our findings suggest that adequate intake levels of choline may have to be reevaluated in different ethnic groups and highlight a possible approach for identifying novel functional SNPs under the influence of dietary selective pressure.—Silver, M. J., Corbin, K. D., Hellenthal, G., da Costa, K.-A., Dominguez-Salas, P., Moore, S. E., Owen, J., Prentice, A. M., Hennig, B. J., Zeisel, S. H. Evidence for negative selection of gene variants that increase dependence on dietary choline in a Gambian cohort.

Background Interindividual epigenetic variation that occurs systemically must be established prior to gastrulation in the very early embryo and, because it is systemic, can be assessed in easily biopsiable tissues. We employ two independent genome-wide approaches to search for such variants. Results First, we screen for metastable epialleles by performing genomewide bisulfite sequencing in peripheral blood lymphocyte (PBL) and hair follicle DNA from two Caucasian adults. Second, we conduct a genomewide screen for genomic regions at which PBL DNA methylation is affected by season of conception in rural Gambia. Remarkably, both approaches identify the genomically imprinted VTRNA2-1 as a top environmentally responsive epiallele. We demonstrate systemic and stochastic interindividual variation in DNA methylation at the VTRNA2-1 differentially methylated region in healthy Caucasian and Asian adults and show, in rural Gambians, that periconceptional environment affects offspring VTRNA2-1 epigenotype, which is stable over at least 10 years. This unbiased screen also identifies over 100 additional candidate metastable epialleles, and shows that these are associated with cis genomic features including transposable elements. Conclusions The non-coding VTRNA2-1 transcript (also called nc886) is a putative tumor suppressor and modulator of innate immunity. Thus, these data indicating environmentally induced loss of imprinting at VTRNA2-1 constitute a plausible causal pathway linking early embryonic environment, epigenetic alteration, and human disease. More broadly, the list of candidate metastable epialleles provides a resource for future studies of epigenetic variation and human disease. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0660-y) contains supplementary material, which is available to authorized users.

Vitamin D is well known for its role in promoting skeletal health. Vitamin D status is determined conventionally by circulating 25-dihydroxyvitamin D (25OHD) concentration. There is evidence indicating that circulating 25OHD concentration is affected by variation in Gc, the gene encoding the vitamin D binding protein (DBP). The composite genotype of two single nucleotide polymorphisms (rs7041 and rs4588) results in different DBP isotypes (Gc1f, Gc1s and Gc2). The protein configurational differences among DBP isotypes affect DBP substrate binding affinity. The aims of this study were to determine 1) Gc variant frequencies in a population from an isolated rural region of The Gambia, West Africa (n = 3129) with year-round opportunity for cutaneous vitamin D synthesis and 2) the effects of Gc variants on 25OHD concentration (n = 237) in a genetically representative sub-group of children (mean (SD) age: 11.9 (4.8) years). The distribution of Gc variants was Gc1f: 0.86, Gc1s: 0.11 and Gc2: 0.03. The mean (SD) concentration of 25OHD was 59.6 (12.9) nmol/L and was significantly higher in those homozygous for Gc1f compared to other Gc variants (60.7 (13.1) vs. 56.6 (12.1) nmol/L, P = 0.03). Plasma 25OHD and 1,25(OH)2D concentration was significantly associated with parathyroid hormone in Gc1f-1f but not in the other Gc variants combined. This study demonstrates that different Gc variants are associated with different 25OHD concentrations in a rural Gambian population. Gc1f-1f, thought to have the highest affinity for 25OHD, had the highest 25OHD concentration compared with lower affinity Gc variants. The considerable difference in Gc1f frequency observed in Gambians compared with other non-West African populations and associated differences in plasma 25OHD concentration, may have implications for the way in which vitamin D status should be interpreted across different ancestral groups., Highlights • We genotyped vitamin D binding protein (Gc) in 3129 rural Gambians. • GC variant distribution is Gc1f: 0.86, Gc1s: 0.11 and Gc2: 0.03. • 25OHD concentrations are higher in Gc1f-1f compared to the other Gc variants.

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function., Author Summary Genes do not act in isolation, but interact in complex networks or pathways. By accounting for such interactions, pathways analysis methods hope to identify aspects of a disease or trait's genetic architecture that might be missed using more conventional approaches. Most existing pathways methods take a univariate approach, in which each variant within a pathway is separately tested for association with the phenotype of interest. These statistics are then combined to assess pathway significance. As a second step, further analysis can reveal important genetic variants within significant pathways. We have previously shown that a joint-modelling approach using a sparse regression model can increase the power to detect pathways influencing a quantitative trait. Here we extend this approach, and describe a method that is able to simultaneously identify pathways and genes that may be driving pathway selection. We test our method using simulations, and apply it to a study searching for pathways and genes associated with high-density lipoprotein cholesterol in two separate East Asian cohorts.