Infant growth restriction is associated with distinct patterns of DNA methylation in human placentas

Abstract

The placenta acts not only as a conduit of nutrient and waste exchange between mother and developing fetus, but also functions as a regulator of the intrauterine environment. Recent work has identified changes in the expression of candidate genes, often through epigenetic alteration, which alter the placenta's function and impact fetal growth. In this study, we used the Illumina Infinium HumanMethylation27 BeadChip array to examine genome-wide DNA methylation patterns in 206 term human placentas. Semi-supervised recursively partitioned mixture modeling was implemented to identify specific patterns of placental DNA methylation that could differentially classify intrauterine growth restriction (IUGR) and small for gestational age (SGA) placentas from appropriate for gestational age (AGA) placentas, and these associations were validated in a masked testing series of samples. Our work demonstrates that patterns of DNA methylation in human placenta are reliably and significantly associated with infant growth and serve as a proof of principle that methylation status in the human term placenta can function as a marker for the intrauterine environment, and could potentially play a critical functional role in fetal development.

Figure 1

Data analysis schematic. Placenta samples were split into training and testing datasets matched with equal proportions of SGA or IUGR samples in each group. Semi-Supervised Recursively Partitioned Mixture Model data analysis was used to rank the methylation of each locus as associated with SGA or IUGR diagnosis.

Figure 2

Association between methylation and birth weight. Volcano plot examining the association between SGA or IUGR diagnosis and methylation extent across all 26,486 autosomal loci examined. Negative log-transformed p values generated from the linear mixed effects model are plotted against the model coefficient (adjusting for gestational age). The area above the solid blue line indicates a p value < 0.05. This coefficient represents the magnitude of the effect of SGA or IUGR status on methylation.

Figure 3

Methylation profiles defined by 22 loci are associated with infant growth status. The Recursively Partitioned Mixture Model-based classification of placenta samples (columns) based on 22 loci (rows) is depicted on the heatmap, with the five classes separated by red lines in the (A) training and (B) testing series. The prevalence of growth restriction or normal births within each of the classes is shown below the heatmap. The Chi-square p value listed below the tables indicates a significant difference in the proportion of SGA participants between classes for both training and testing datasets.