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Background: Cardiometabolic conditions in adulthood are more common in children born SGA1. The relationship of the transcriptome (gene expression) and epigenome (DNA methylation) to birth size and the future development of cardiometabolic disease has not been characterized. Aims: To identify I) the relationship between epigenome at age 0, 7 and 17 years, transcriptome at age 9 years and birth size in a normal population; II) links between the transcriptome and epigenome in childhood and adult cardiometabolic risk. Study Design: Normal children (n=6487) from the Avon Longitudinal Study of Parents and Children were assigned to groups based on birth size using bodyweight (BW) and gestation and divided into groups using the population 10th centile. Adverse cardiometabolic risk at age 17 years was defined by the National Heart Lung and Blood Institute criteria of prehypertension using systolic and diastolic blood pressure as well as HDL and LDL2. Blood transcriptome at age 9 and blood epigenome at age 0, 7, and 17 years and were available from 980 and 947 children, respectively. Hypernetworks were used to integrate differentially expressed genes in the transcriptome (DEGs) and differentially methylated points (DMPs) in the epigenome, identifying functional links. Random Forest, a machine learning approach, was used to determine the predictive value of ‘omic data presented as the area under the curve (AUC) of the receiver operating characteristic. Results: Pre-hypertensive participants at age 17 years were distinguished from normotensive participants and this group was enriched for children born small who caught up by age 7 years (155/611 unhealthy/healthy SGA compared to 1979/12746 in all other BW groups; 1.6-fold, p&amp;lt;1x10-5). This group had a greater height velocity during their catch-up period than the normotensive participants (1.2-fold, p=0.027). Hypernetwork integration of ‘omic data identified a functional relationship between 55 DEGs at age 9 years and DMPs at age 7 years. Random forest analysis was able to accurately predict the presence of pre-hypertensive young adults from the age 9 transcriptome (AUC: 0.973). Using a gene-level contraction of DMPs which map to the 55 DEGs (i.e. cis-DMPs), we demonstrated accurate classification of pre-hypertensive young adults from their blood methylome at age 0 (AUC [95% CI]: 0.92 [0.89-0.95]), 7 (0.90 [0.87-0.93]), and 17 (0.91 [0.88-0.94]) years. Conclusions: Through the integration of transcriptome and epigenome, we have identified a set of genes with an epigenomic and transcriptomic signature which predict pre-hypertension in children born SGA who catch up. Specifically, we have shown that the associated epigenomic signature tracks from birth to early adulthood, indicating the possibility of early detection of risk and primordial prevention. 1 Barker etal. (1988) BMJ 297(6641):134-135. 2 Chobanian etal. (2003) JAMA 289(19):2560-2571.

journal of the endocrine society

An Epigenomic Signature in Children Born Small for Gestational Age (SGA) With “Catch-up” Growth Is Present From Birth and Predicts Early Adulthood Pre-Hypertension