Choice of surrogate tissue influences neonatal EWAS findings

Abstract

Background: Epigenomes are tissue specific and thus the choice of surrogate tissue can play a critical role in interpreting neonatal epigenome-wide association studies (EWAS) and in their extrapolation to target tissue. To develop a better understanding of the link between tissue specificity and neonatal EWAS, and the contributions of genotype and prenatal factors, we compared genome-wide DNA methylation of cord tissue and cord blood, two of the most accessible surrogate tissues at birth.

Methods: In 295 neonates, DNA methylation was profiled using Infinium HumanMethylation450 beadchip arrays. Sites of inter-individual variability in DNA methylation were mapped and compared across the two surrogate tissues at birth, i.e., cord tissue and cord blood. To ascertain the similarity to target tissues, DNA methylation profiles of surrogate tissues were compared to 25 primary tissues/cell types mapped under the Epigenome Roadmap project. Tissue-specific influences of genotype on the variable CpGs were also analyzed. Finally, to interrogate the impact of the in utero environment, EWAS on 45 prenatal factors were performed and compared across the surrogate tissues.

Results: Neonatal EWAS results were tissue specific. In comparison to cord blood, cord tissue showed higher inter-individual variability in the epigenome, with a lower proportion of CpGs influenced by genotype. Both neonatal tissues were good surrogates for target tissues of mesodermal origin. They also showed distinct phenotypic associations, with effect sizes of the overlapping CpGs being in the same order of magnitude.

Conclusions: The inter-relationship between genetics, prenatal factors and epigenetics is tissue specific, and requires careful consideration in designing and interpreting future neonatal EWAS.

Trial registration: This birth cohort is a prospective observational study, designed to study the developmental origins of health and disease, and was retrospectively registered on 1 July 2010 under the identifier NCT01174875 .

Keywords: DNA methylation; Epigenome-wide association study; Genotype; Neonate; Prenatal factors; Tissue-specificity.

Conflict of interest statement

Consent for publication

Not applicable.

Competing interests

YSC and KMG have received reimbursement for speaking at conferences sponsored by companies selling nutritional products. They are part of an academic consortium that has received research funding from Abbott Nutrition, Nestec, and Danone. The other authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1

Infant cord tissue showed more inter-individual variation than infant cord blood: proportion of CpGs that showed inter-individual variation and interquartile range (IQR) in DNA methylation. a Pie chart shows the proportion of CpGs for four distinct categories: (1) CpGs which showed inter-individual variation in both tissues, (2) CpGs which showed inter-individual variation only in infant cord blood, (3) CpGs which showed inter-individual variation only in infant cord tissue, and (4) CpGs which did not show inter-individual variation in either tissue. A total of 239,560 CpGs passed quality control in both datasets. b Plot of proportion of CpGs (vertical axis) in each tissue (out of 239,560 CpGs) with DNA methylation IQR greater than or equal to the value specified on the horizontal axis. c Boxplots show the distribution of the DNA methylation IQR, for CpGs in infant cord tissue (bright orange) and infant cord blood (bright blue), respectively, for each of the four categories. Outliers are not shown in the boxplots. A CpG was defined to show inter-individual variation if the DNA methylation range (maximum–minimum, excluding outliers) was greater than 10% and DNA methylation 99th percentile–1st percentile was greater than 5%

Fig. 2

Infant cord tissue is a better surrogate for primary tissues of mesenchymal stem cell (MSC)-derived mesodermic germinal origins, while infant cord blood is a better surrogate for primary tissues of hematopoietic stem cell (HSC)-derived mesodermic germinal origins: hierarchical clustering of GUSTO tissues (cord tissue, cord blood) with 25 primary tissues/cells profiled using reduced representation bisulfite sequencing in the Epigenome Roadmap project. Infant cord tissue clustered more closely with primary tissues of MSC-derived mesodermic germinal origins, while infant cord blood clustered more closely with primary tissues of HSC-derived mesodermic germinal origins. Left panel shows heatmap of DNA methylation values, with each row representing each tissue type and each column representing each CpG. Color changes from yellow to blue as DNA methylation changes from 0% to 100%. Right panel of plot shows dendrogram, with tissue types of ectodermic, endodermic, HSC-derived mesodermic, and MSC-derived mesodermic germinal origins represented in light pink, light purple, light turquoise, and light orange, respectively; GUSTO cord tissue and cord blood are represented in bright orange and bright blue, respectively. DNA methylation values from GUSTO tissues were generated using Infinium 450 K array (for each CpG and tissue type, the median value across all samples was used). For tissues/cells profiled by the Epigenome Roadmap project, only DNA methylation sites with a minimum reads coverage of 30X were retained and reads from both strands were combined. Hierarchical clustering was performed using only CpG sites that passed quality control filtering in GUSTO tissues, were non-missing in at least 10 out of the 25 Epigenome Roadmap samples, and had interquartile range greater than 10% across different Epigenome Roadmap tissues/cells

Fig. 3

SNPs explained a greater proportion of inter-individual variation in DNA methylation in infant cord blood (CB) than in infant cord tissue (CT): SNP-associated CpGs detected in each infant tissue. a Pie charts show the percentage of CpGs in each infant tissue whose inter-individual variation could be explained by SNPs (out of all CpGs which showed inter-individual variation in the infant tissue). A CpG whose inter-individual variation could be explained by SNPs (SNP-associated) was defined to be one where the most significant association between the CpG and cis-SNPs (all SNPs on the same chromosome as CpG) attained a P value < 5 × 10–8, the commonly used Bonferroni threshold for genome-wide association studies (corresponding to testing for 106 independent SNPs across the genome at a family-wise Type 1 error rate of 0.05). b Overlap between SNP-associated, non-SNP-associated (but variable), and non-variable CpGs in the two tissues. Only CpGs which showed inter-individual variation in at least one tissue were included (N = 98,124). Examining each tissue separately, each of these 98,124 CpGs can either be SNP-associated, not SNP-associated, or not variable in each tissue. The number of CpGs in each of these three sets in each tissue is shown in the bottom left bar chart (for each tissue the number of CpGs from the three sets will sum to 98,124). Collectively, the 98,124 CpGs can be grouped into eight categories. The bottom right panel identifies each of these eight categories, with the solid black dots representing the sets being considered. For example, the extreme right column identifies the group of CpGs that are SNP-associated in both tissues. The top bar chart shows the number of CpGs in each of these eight categories. For example, 7822 CpGs were SNP-associated in both tissues

Fig. 4

Prenatal factors (PFs) explained a similar proportion of inter-individual variation in infant cord blood (CB) and infant cord tissue (CT): CpGs where the inter-individual variation in DNA methylation were explained by PFs. a Heatmap shows the pairwise Spearman correlation (absolute value) between 45 PFs. Each row/column represents each PF. Color changes from white to blue as correlation changes from zero to one. b Pie charts show the percentage of CpGs in each infant tissue whose inter-individual variation could be explained by PFs (out of all CpGs, which showed inter-individual variation in the infant tissue). A CpG whose inter-individual variation could be explained by PFs was defined to be one where the most significant association between the CpG and all 45 PFs attained a P value < 1 × 10–3, the Bonferroni threshold for testing 45 PFs at a family-wise Type 1 error rate of 0.05. c Overlap between PF-associated, non-PF-associated (but variable), and non-variable CpGs in the two tissues. Only CpGs which showed inter-individual variation in at least one tissue were included (N = 98,124). Examining each tissue separately, each of these 98,124 CpGs can either be PF-associated, non-PF-associated, or not variable in each tissue. The number of CpGs in each of these three sets in each tissue is shown in the bottom left bar chart. Collectively, the 98,124 CpGs can be grouped into eight categories. The bottom right panel identifies each of these eight categories, with the solid black dots representing the sets being considered. The top bar chart shows the number of CpGs in each of these eight categories