A transcriptomic signature that predicts pre-hypertension in adolescence and higher systolic blood pressure in childhood
Suboptimal fetal growth (SFG), being born small-for-gestational-age (SGA), and catch-up (CU) growth are individually and together linked to cardiometabolic (CM) risks. However not all develop adverse outcomes. This study aimed to validate a transcriptomic signature to identify individuals at greatest CM risk. Using National Heart Lung and Blood Institute criteria to define CM risk, healthy and prehypertensive 17-year-olds were identified in the ALSPAC (UK) childhood cohort. Epigenomic and transcriptomic differences were analysed. A hypernetwork identified functionally related genes, which were used in random forest classification to predict prehypertensive phenotypes. The BabyGRO (UK) cohort included 80 children aged 3–7 years, born at term following pregnancies with SFG risks. Anthropometric, CM markers and transcriptomic profiles were collected, fetal and childhood weight trajectories and their relationship to CM markers assessed, and transcriptome used for prediction. CU-SGA individuals in ALSPAC were 1.6 times more likely than all others to be prehypertensive at 17 years (p<1x10?5). A 42-gene hypernetwork cluster was highly predictive of prehypertension (AUC 0.984, error rate 5.4%). In BabyGRO, 20 of these genes accurately predicted higher systolic blood pressure (AUC 0.971, error rate 3.6%). This transcriptomic signature could help identify children with adverse pre- and postnatal growth who may develop prehypertension. Overall design: RNA-seq profiling of blood samples from children aged three-to-seven following detection of risk of FGR