Hong Pan

The effect of genotype and in utero environment on interindividual variation in neonate DNA methylomes

Integrating the genotype with epigenetic marks holds the promise of better understanding the biology that underlies the complex interactions of inherited and environmental components that define the developmental origins of a range of disorders. The quality of the in utero environment significantly influences health over the lifecourse. Epigenetics, and in particular DNA methylation marks, have been postulated as a mechanism for the enduring effects of the prenatal environment. Accordingly, neonate methylomes contain molecular memory of the individual in utero experience. However, interindividual variation in methylation can also be a consequence of DNA sequence polymorphisms that result in methylation quantitative trait loci (methQTLs) and, potentially, the interaction between fixed genetic variation and environmental influences. We surveyed the genotypes and DNA methylomes of 237 neonates and found 1423 punctuate regions of the methylome that were highly variable across individuals, termed variably methylated regions (VMRs), against a backdrop of homogeneity. MethQTLs were readily detected in neonatal methylomes, and genotype alone best explained ∼25% of the VMRs. We found that the best explanation for 75% of VMRs was the interaction of genotype with different in utero environments, including maternal smoking, maternal depression, maternal BMI, infant birth weight, gestational age, and birth order. Our study sheds new light on the complex relationship between biological inheritance as represented by genotype and individual prenatal experience and suggests the importance of considering both fixed genetic variation and environmental factors in interpreting epigenetic variation.

Measuring the methylome in clinical samples: Improved processing of the Infinium Human Methylation450 BeadChip Array

The Infinium Human Methylation450 BeadChip ArrayTM (Infinium 450K) is an important tool for studying epigenetic patterns associated with disease. This array offers a high-throughput, low cost alternative to more comprehensive sequencing-based methodologies. Here we compare data generated by interrogation of the same seven clinical samples by Infinium 450K and reduced representation bisulfite sequencing (RRBS). This is the largest data set comparing Infinium 450K array to the comprehensive RRBS methodology reported so far. We show good agreement between the two methodologies. A read depth of four or more reads in the RRBS data was sufficient to achieve good agreement with Infinium 450K. However, we observe that intermediate methylation values (20–80%) are more variable between technologies than values at the extremes of the bimodal methylation distribution. We describe careful processing of Infinium 450K data to correct for known limitations and batch effects. Using methodologies proposed by others and newly implemented and combined in this report, agreement of Infinium 450K data with independent techniques can be vastly improved.

HIF3A association with adiposity: the story begins before birth

Aim: Determine if the association of HIF3A DNA methylation with weight and adiposity is detectable early in life. Material & methods: We determined HIF3A genotype and DNA methylation patterns (on hybridization arrays) in DNA extracted from umbilical cords of 991 infants. Methylation levels at three CpGs in the HIF3A first intron were related to neonatal and infant anthropometry and to genotype at nearby polymorphic sites. Results & conclusion: Higher methylation levels at three previously described HIF3A CpGs were associated with greater infant weight and adiposity. The effect sizes were slightly smaller than those reported for adult BMI. There was also an interaction within cis-genotype. The association between higher DNA methylation at HIF3A and increased adiposity is present in neonates. In this study, no particular prenatal factor strongly influenced HIF3A hypermethylation. Our data nonetheless suggest shared prenatal influences on HIF3A methylation and adiposity.

Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism influences the association of the methylome with maternal anxiety and neonatal brain volumes

Early life environments interact with genotype to determine stable phenotypic outcomes. Here we examined the influence of a variant in the brain-derived neurotropic factor (BDNF) gene (Val66Met), which underlies synaptic plasticity throughout the central nervous system, on the degree to which antenatal maternal anxiety associated with neonatal DNA methylation. We also examined the association between neonatal DNA methylation and brain substructure volume, as a function of BDNF genotype. Infant, but not maternal, BDNF genotype dramatically influences the association of antenatal anxiety on the epigenome at birth as well as that between the epigenome and neonatal brain structure. There was a greater impact of antenatal maternal anxiety on the DNA methylation of infants with the methionine (Met)/Met compared to both Met/valine (Val) and Val/Val genotypes. There were significantly more cytosine-phosphate-guanine sites where methylation levels covaried with right amygdala volume among Met/Met compared with both Met/Val and Val/Val carriers. In contrast, more cytosine-phosphate-guanine sites covaried with left hippocampus volume in Val/Val infants compared with infants of the Met/Val or Met/Met genotype. Thus, antenatal Maternal Anxiety × BDNF Val66Met Polymorphism interactions at the level of the epigenome are reflected differently in the structure of the amygdala and the hippocampus. These findings suggest that BDNF genotype regulates the sensitivity of the methylome to early environment and that differential susceptibility to specific environmental conditions may be both tissue and function specific.

Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood

Childhood obesity is a major public health issue. Here we investigated whether differential DNA methylation was associated with childhood obesity. We studied DNA methylation profiles in whole blood from 78 obese children (mean BMI Z-score: 2.6) and 71 age- and sex-matched controls (mean BMI Z-score: 0.1). DNA samples from obese and control groups were pooled and analyzed using the Infinium HumanMethylation450 BeadChip array. Comparison of the methylation profiles between obese and control subjects revealed 129 differentially methylated CpG (DMCpG) loci associated with 80 unique genes that had a greater than 10% difference in methylation (P-value < 0.05). The top pathways enriched among the DMCpGs included developmental processes, immune system regulation, regulation of cell signaling, and small GTPase-mediated signal transduction. The associations between the methylation of selected DMCpGs with childhood obesity were validated using sodium bisulfite pyrosequencing across loci within the FYN, PIWIL4, and TAOK3 genes in individual subjects. Three CpG loci within FYN were hypermethylated in obese individuals (all P < 0.01), while obesity was associated with lower methylation of CpG loci within PIWIL4 (P = 0.003) and TAOK3 (P = 0.001). After building logistic regression models, we determined that a 1% increase in methylation in TAOK3, multiplicatively decreased the odds of being obese by 0.91 (95% CI: 0.86 – 0.97), and an increase of 1% methylation in FYN CpG3, multiplicatively increased the odds of being obese by 1.03 (95% CI: 0.99 – 1.07). In conclusion, these findings provide evidence that childhood obesity is associated with specific DNA methylation changes in whole blood, which may have utility as biomarkers of obesity risk.

Comparison of Methyl-capture Sequencing vs. Infinium 450K methylation array for methylome analysis in clinical samples

ABSTRACT Interindividual variability in the epigenome has gained tremendous attention for its potential in pathophysiological investigation, disease diagnosis, and evaluation of clinical intervention. DNA methylation is the most studied epigenetic mark in epigenome-wide association studies (EWAS) as it can be detected from limited starting material. Infinium 450K methylation array is the most popular platform for high-throughput profiling of this mark in clinical samples, as it is cost-effective and requires small amounts of DNA. However, this method suffers from low genome coverage and errors introduced by probe cross-hybridization. Whole-genome bisulfite sequencing can overcome these limitations but elevates the costs tremendously. Methyl-Capture Sequencing (MC Seq) is an attractive intermediate solution to increase the methylome coverage in large sample sets. Here we first demonstrate that MC Seq can be employed using DNA amounts comparable to the amounts used for Infinium 450K. Second, to provide guidance when choosing between the 2 platforms for EWAS, we evaluate and compare MC Seq and Infinium 450K in terms of coverage, technical variation, and concordance of methylation calls in clinical samples. Last, since the focus in EWAS is to study interindividual variation, we demonstrate the utility of MC Seq in studying interindividual variation in subjects from different ethnicities.

Transcriptome changes affecting Hedgehog and cytokine signalling in the umbilical cord: implications for disease risk.

Background Babies born at lower gestational ages or smaller birthweights have a greater risk of poorer health in later life. Both the causes of these sub-optimal birth outcomes and the mechanism by which the effects are transmitted over decades are the subject of extensive study. We investigated whether a transcriptomic signature of either birthweight or gestational age could be detected in umbilical cord RNA. Methods The gene expression patterns of 32 umbilical cords from Singaporean babies of Chinese ethnicity across a range of birthweights (1698–4151 g) and gestational ages (35–41 weeks) were determined. We confirmed the differential expression pattern by gestational age for 12 genes in a series of 127 umbilical cords of Chinese, Malay and Indian ethnicity. Results We found that the transcriptome is substantially influenced by gestational age; but less so by birthweight. We show that some of the expression changes dependent on gestational age are enriched in signal transduction pathways, such as Hedgehog and in genes with roles in cytokine signalling and angiogenesis. We show that some of the gene expression changes we report are reflected in the epigenome. Conclusions We studied the umbilical cord which is peripheral to disease susceptible tissues. The results suggest that soma-wide transcriptome changes, preserved at the epigenetic level, may be a mechanism whereby birth outcomes are linked to the risk of adult metabolic and arthritic disease and suggest that greater attention be given to the association between premature birth and later disease risk.

Gene, Environment and Methylation (GEM): a tool suite to efficiently navigate large scale epigenome wide association studies and integrate genotype and interaction between genotype and environment.

BackgroundThe interplay among genetic, environment and epigenetic variation is not fully understood. Advances in high-throughput genotyping methods, high-density DNA methylation detection and well-characterized sample collections, enable epigenetic association studies at the genomic and population levels (EWAS). The field has extended to interrogate the interaction of environmental and genetic (GxE) influences on epigenetic variation. Also, the detection of methylation quantitative trait loci (methQTLs) and their association with health status has enhanced our knowledge of epigenetic mechanisms in disease trajectory. However analysis of this type of data brings computational challenges and there are few practical solutions to enable large scale studies in standard computational environments.ResultsGEM is a highly efficient R tool suite for performing epigenome wide association studies (EWAS). GEM provides three major functions named GEM_Emodel, GEM_Gmodel and GEM_GxEmodel to study the interplay of Gene, Environment and Methylation (GEM). Within GEM, the pre-existing “Matrix eQTL” package is utilized and extended to study methylation quantitative trait loci (methQTL) and the interaction of genotype and environment (GxE) to determine DNA methylation variation, using matrix based iterative correlation and memory-efficient data analysis. Benchmarking presented here on a publicly available dataset, demonstrated that GEM can facilitate reliable genome-wide methQTL and GxE analysis on a standard laptop computer within minutes.ConclusionsThe GEM package facilitates efficient EWAS study in large cohorts. It is written in R code and can be freely downloaded from Bioconductor at https://www.bioconductor.org/packages/GEM/.

Alterations to DNA methylation and expression of CXCL14 are associated with suboptimal birth outcomes

CXCL14 is a chemokine that has previously been implicated in insulin resistance in mice. In humans, the role of CXCL14 in metabolic processes is not well established, and we sought to determine whether CXCL14 is a risk susceptibility gene important in fetal programming of metabolic disease. For this purpose, we investigated whether CXCL14 is differentially regulated in human umbilical cords of infants with varying birth weights. We found an elevated expression of CXCL14 in human low birth weight (LBW) cords, as well as in cords from nutritionally restricted Macaca fascicularis macaques. To further analyze the regulatory mechanisms underlying the expression of CXCL14, we examined CXCL14 in umbilical cord-derived mesenchymal stem cells (MSCs) that provide an in vitro cell-based system amenable to experimental manipulation. Using both whole frozen cords and MSCs, we determined that site-specific CpG methylation in the CXCL14 promoter is associated with altered expression, and that changes in methylation are evident in LBW infant-derived umbilical cords that may indicate future metabolic compromise through CXCL14.

Long-chain polyunsaturated fatty acids, gestation duration, and birth size: a Mendelian randomization study using fatty acid desaturase variants

Background In randomized trials, supplementation of n-3 (ω-3) long-chain polyunsaturated fatty acids (LC-PUFAs) during pregnancy has resulted in increased size at birth, which is attributable to longer gestation. Objective We examined this finding by using a Mendelian randomization approach utilizing fatty acid desaturase (FADS) gene variants affecting LC-PUFA metabolism. Design As part of a tri-ethnic mother-offspring cohort in Singapore, 35 genetic variants in FADS1, FADS2, and FADS3 were genotyped in 898 mothers and 1103 offspring. Maternal plasma n-3 and n-6 PUFA concentrations at 26-28 wk of gestation were measured. Gestation duration was derived from an ultrasound dating scan in early pregnancy and from birth date. Birth length and weight were measured. Eight FADS variants were selected through a tagging-SNP approach and examined in association with PUFA concentrations, gestation duration among spontaneous labors, and birth size with the use of ethnicity-adjusted linear regressions and survival models that accounted for the competing risks of induced labor and prelabor cesarean delivery. Results Maternal FADS1 variant rs174546, tagging for 8 other variants located on FADS1 and FADS2, was strongly related to plasma n-6 but not n-3 LC-PUFA concentrations. Offspring and maternal FADS3 variants were associated with gestation duration among women who had spontaneous labor: each copy of rs174450 minor allele C was associated with a shorter gestation by 2.2 d (95% CI: 0.9, 3.4 d) and 1.9 d (0.7, 3.0 d) for maternal and offspring variants, respectively. In survival models, rs174450 minor allele homozygotes had reduced time to delivery after spontaneous labor compared with major allele homozygotes [HR (95% CI): 1.51 (1.18, 1.95) and 1.51 (1.20, 1.89) for mothers and offspring, respectively]. Conclusions With the use of a Mendelian randomization approach, we observed associations between FADS variants and gestation duration. This suggests a potential role of LC-PUFAs in gestation duration. This trial was registered at http://www.clinicaltrials.gov as NCT01174875.