Endocrine Abstracts

Background: Cardiometabolic risk is linked to being small for gestational age (SGA, birthweight <-2SDS). Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), an ‘omic signature in SGA catch-up children predicts pre-hypertension in adolescence. Suboptimal fetal growth (SFG) alone may be linked with greater cardiometabolic risk. Therefore, we focused on cardiometabolic risk in children born following pregnancies at higher risk for SFG, irrespective of birthweight.

Aim: To validate the predictive ability of an ALSPAC-derived ‘omic signature for pre-hypertension, in a Manchester cohort of children whose mothers had displayed higher risk of SFG in pregnancy.

Methods: We recruited 81 children aged 3-6 years, following term pregnancies at increased risk of SFG based on adverse maternal antenatal serology (e.g. low pregnancy associated plasma protein-A). Body mass index (BMI) SDS, abdominal circumference (AC), mid-upper arm circumference (MUAC), %fat, systolic blood pressure (SBP) and brachial augmentation index (AI) were recorded. Fasting blood samples for cardiometabolic markers and transcriptomic (gene expression) analyses were collected (n=31). Δfetalwt ([birthweight centile minus 23-week estimated fetal weight centile]/days) and Δchildwt ([child weight centile minus birthweight centile]/years) were divided into quartiles and differences in cardiometabolic markers compared. Random forest was used to determine the predictive ability of the ALSPAC-derived ‘omic signature for Q4 childhood BP in the BabyGRO cohort.

Results: 69% (56/81) had Δfetalwt <0, but only 12% (10/81) were born SGA. SBP was higher and HDL lower in Δfetal Q1 (lowest intrauterine weight gain) vs Q4 (P<0.05). SBP, BMI SDS, AC, MUAC, AI and %fat were higher in Δchildwt Q4 (highest childhood weight gain) vs Q1 (P<0.05). Transcriptomic data were available for expression of 33 of 47 ALSPAC genes predictive of pre-hypertension. Random forest accurately predicted child SBP Q4 from Q1-3 (out of bag AUC 0.98, error rate 3.9%).

Conclusion: Pre-hypertension gene expression demonstrated in SGA children with catch-up growth predicts higher SBP within this cohort enriched for SFG, but where only a minority were SGA-born. This ‘omic signature could aid early identification of non-SGA infants with prehypertension risk, who may require BP monitoring from early-life onwards.