DNA methylation signatures in cord blood associated with maternal gestational weight gain: results from the ALSPAC cohort.

BACKGROUND: Epigenetic changes could mediate the association of maternal pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) with adverse offspring outcomes. However, studies in humans are lacking. Here, we examined the association of maternal pre-pregnancy BMI and GWG in different periods of pregnancy with cytosine-guanine (CpG) dinucleotide site methylation differences in newborn cord blood DNA from 88 participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort using the Illumina GoldenGate Panel I. Pyrosequencing was used for validation of the top associated locus and for replication in 170 non-overlapping mother-offspring pairs from the ALSPAC cohort. RESULTS: After correction for multiple testing greater GWG in early pregnancy (between 0 to 18 weeks of gestation) was associated with increased DNA methylation levels in four CpG sites at MMP7, KCNK4, TRPM5 and NFKB1 genes (difference in methylation >5% per 400 g/week greater GWG) (q values 0.023 -0.065). Pre-pregnancy BMI and GWG in mid- or late pregnancy were not associated with differential DNA methylation at any CpG site. Pyrosequencing showed that greater GWG in early pregnancy was associated with increased DNA methylation levels at the top associated CpG site at MMP7, although association did not reach statistical significance (p = 0.302). Greater GWG in mid- (p = 0.167) and late-pregnancy (p = 0.037) were also associated with increased DNA methylation levels at the MMP7 CpG site. In addition, newborns of mothers who exceeded the IoM-recommended GWG had higher DNA methylation levels at the MMP7 CpG site than those of mothers with IoM-recommended GWG (p = 0.080). We failed to replicate findings. CONCLUSIONS: Greater GWG in early pregnancy was associated with increased methylation at CpG sites at MMP7, KCNK4, TRPM5 and NFKB1 genes in offspring cord blood DNA. The specific association of GWG in early pregnancy with the top associated CpG site at MMP7 was not validated using Pyrosequencing and it did not replicate. However, given the potential functional relevancy of the four identified loci, we advocate further exploration of them in larger studies.

Influence of DNMT genotype on global and site specific DNA methylation patterns in neonates and pregnant women.

This study examines the relationship between common genetic variation within DNA methyltransferase genes and inter-individual variation in DNA methylation. Eleven polymorphisms spanning DNMT1 and DNMT3B were genotyped. Global and gene specific (IGF2, IGFBP3, ZNT5) DNA methylation was quantified by LUMA and bisulfite Pyrosequencing assays, respectively, in neonatal cord blood and in maternal peripheral blood. Associations between maternal genotype and maternal methylation (n (≈) 333), neonatal genotype and neonatal methylation (n (≈) 454), and maternal genotype and neonatal methylation (n (≈) 137) were assessed. The findings of this study provide some support to the hypothesis that genetic variation in DNA methylating enzymes influence DNA methylation at global and gene-specific levels; however observations were not robust to correction for multiple testing. More comprehensive analysis of the influence of genetic variation on global and site specific DNA methylation is warranted.

Genetic and non-genetic influences during pregnancy on infant global and site specific DNA methylation: role for folate gene variants and vitamin B12.

Inter-individual variation in patterns of DNA methylation at birth can be explained by the influence of environmental, genetic and stochastic factors. This study investigates the genetic and non-genetic determinants of variation in DNA methylation in human infants. Given its central role in provision of methyl groups for DNA methylation, this study focuses on aspects of folate metabolism. Global (LUMA) and gene specific (IGF2, ZNT5, IGFBP3) DNA methylation were quantified in 430 infants by Pyrosequencing®. Seven polymorphisms in 6 genes (MTHFR, MTRR, FOLH1, CßS, RFC1, SHMT) involved in folate absorption and metabolism were analysed in DNA from both infants and mothers. Red blood cell folate and serum vitamin B(12) concentrations were measured as indices of vitamin status. Relationships between DNA methylation patterns and several covariates viz. sex, gestation length, maternal and infant red cell folate, maternal and infant serum vitamin B(12), maternal age, smoking and genotype were tested. Length of gestation correlated positively with IGF2 methylation (rho = 0.11, p = 0.032) and inversely with ZNT5 methylation (rho = -0.13, p = 0.017). Methylation of the IGFBP3 locus correlated inversely with infant vitamin B(12) concentration (rho = -0.16, p = 0.007), whilst global DNA methylation correlated inversely with maternal vitamin B(12) concentrations (rho = 0.18, p = 0.044). Analysis of common genetic variants in folate pathway genes highlighted several associations including infant MTRR 66G>A genotype with DNA methylation (χ(2) = 8.82, p = 0.003) and maternal MTHFR 677C>T genotype with IGF2 methylation (χ(2) = 2.77, p = 0.006). These data support the hypothesis that both environmental and genetic factors involved in one-carbon metabolism influence DNA methylation in infants. Specifically, the findings highlight the importance of vitamin B(12) status, infant MTRR genotype and maternal MTHFR genotype, all of which may influence the supply of methyl groups for DNA methylation. In addition, gestational length appears to be an important determinant of infant DNA methylation patterns.

Bioinformatic selection of putative epigenetically regulated loci associated with obesity using gene expression data.

There is considerable interest in defining the relationship between epigenetic variation and the risk of common complex diseases. Strategies which assist in the prioritisation of target loci that have the potential to be epigenetically regulated might provide a useful approach in identifying concrete examples of epigenotype-phenotype associations. Focusing on the postulated role of epigenetic factors in the aetiopathogenesis of obesity this report outlines an approach utilising gene expression data and a suite of bioinformatic tools to prioritise a list of target candidate genes for more detailed experimental scrutiny. Gene expression microarrays were performed using peripheral blood RNA from children aged 11-13years selected from the Newcastle Preterm Birth Growth Study which were grouped by body mass index (BMI). Genes showing ≥2.0 fold differential expression between low and high BMI groups were selected for in silico analysis. Several bioinformatic tools were used for each following step; 1) a literature search was carried out to identify whether the differentially expressed genes were associated with adiposity phenotypes. Of those obesity-candidate genes, putative epigenetically regulated promoters were identified by 2) defining the promoter regions, 3) then by selecting promoters with a CpG island (CGI), 4) and then by identifying any transcription factor binding modules covering CpG sites within the CGI. This bioinformatic processing culminated in the identification of a short list of target obesity-candidate genes putatively regulated by DNA methylation which can be taken forward for experimental analysis. The proposed workflow provides a flexible, versatile and low cost methodology for target gene prioritisation that is applicable to multiple species and disease contexts.

DNA methylation patterns in cord blood DNA and body size in childhood.

BACKGROUND: Epigenetic markings acquired in early life may have phenotypic consequences later in development through their role in transcriptional regulation with relevance to the developmental origins of diseases including obesity. The goal of this study was to investigate whether DNA methylation levels at birth are associated with body size later in childhood. PRINCIPAL FINDINGS: A study design involving two birth cohorts was used to conduct transcription profiling followed by DNA methylation analysis in peripheral blood. Gene expression analysis was undertaken in 24 individuals whose biological samples and clinical data were collected at a mean ± standard deviation (SD) age of 12.35 (0.95) years, the upper and lower tertiles of body mass index (BMI) were compared with a mean (SD) BMI difference of 9.86 (2.37) kg/m(2). This generated a panel of differentially expressed genes for DNA methylation analysis which was then undertaken in cord blood DNA in 178 individuals with body composition data prospectively collected at a mean (SD) age of 9.83 (0.23) years. Twenty-nine differentially expressed genes (>1.2-fold and p<10(-4)) were analysed to determine DNA methylation levels at 1-3 sites per gene. Five genes were unmethylated and DNA methylation in the remaining 24 genes was analysed using linear regression with bootstrapping. Methylation in 9 of the 24 (37.5%) genes studied was associated with at least one index of body composition (BMI, fat mass, lean mass, height) at age 9 years, although only one of these associations remained after correction for multiple testing (ALPL with height, p(Corrected) = 0.017). CONCLUSIONS: DNA methylation patterns in cord blood show some association with altered gene expression, body size and composition in childhood. The observed relationship is correlative and despite suggestion of a mechanistic epigenetic link between in utero life and later phenotype, further investigation is required to establish causality.

People of the British Isles: preliminary analysis of genotypes and surnames in a UK-control population.

There is a great deal of interest in a fine-scale population structure in the UK, both as a signature of historical immigration events and because of the effect population structure may have on disease association studies. Although population structure appears to have a minor impact on the current generation of genome-wide association studies, it is likely to have a significant part in the next generation of studies designed to search for rare variants. A powerful way of detecting such structure is to control and document carefully the provenance of the samples involved. In this study, we describe the collection of a cohort of rural UK samples (The People of the British Isles), aimed at providing a well-characterised UK-control population that can be used as a resource by the research community, as well as providing a fine-scale genetic information on the British population. So far, some 4000 samples have been collected, the majority of which fit the criteria of coming from a rural area and having all four grandparents from approximately the same area. Analysis of the first 3865 samples that have been geocoded indicates that 75% have a mean distance between grandparental places of birth of 37.3 km, and that about 70% of grandparental places of birth can be classed as rural. Preliminary genotyping of 1057 samples demonstrates the value of these samples for investigating a fine-scale population structure within the UK, and shows how this can be enhanced by the use of surnames.

Postnatal growth and DNA methylation are associated with differential gene expression of the TACSTD2 gene and childhood fat mass.

Rapid postnatal growth is associated with increased risk of childhood adiposity. The aim of this study was to establish whether this pathway is mediated by altered DNA methylation and gene expression. Two distinct cohorts, one preterm (n=121) and one term born (n=6,990), were studied. Exploratory analyses were performed using microarrays to identify differentially expressed genes in whole blood from children defined as "slow" (n=10) compared with "rapid" (n=10) postnatal (term to 12 weeks corrected age) growers. Methylation within the identified TACSTD2 gene was measured in both cohorts, and rs61779296 genotype was determined by Pyrosequencing or imputation and analyzed in relation to body composition at 9-15 years of age. In cohort 1, TACSTD2 expression was inversely correlated with methylation (P=0.016), and both measures were associated with fat mass (expression, P=0.049; methylation, P=0.037). Although associated with gene expression (cohort 1, P=0.008) and methylation (cohort 1, P=2.98×10(-11); cohort 2, P=3.43×10(-15)), rs61779296 was not associated with postnatal growth or fat mass in either cohort following multiple regression analysis. Hence, the lack of association between fat mass and a methylation proxy SNP suggests that reverse causation or confounding may explain the initial association between fat mass and gene regulation. Noncausal methylation patterns may still be useful predictors of later adiposity.