ESPE Abstracts

Background: Cardiometabolic (CM) risk is linked to being small for gestational age (SGA, birthweight <-2SDS). Fetal growth restriction (FGR) may not result in SGA. We focused on potential CM risk in children born following pregnancies at higher risk for FGR.

Aims: To identify associations between fetal and childhood weight trajectory quartiles and CM risk markers. 2.To define molecular pathways potentially associated with CM risk.

Methods: We recruited 81 children aged 3-6 years, from term pregnancies at increased risk of FGR. 54% were male and 32% Non-White. 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. For 31, who provided consent, fasting blood samples were collected for CM markers (insulin & high-density lipoprotein [HDL]), metabolomic and transcriptomic analyses. Standardised weight changes; ∆fetalwt ([birthweight minus 23-week estimated fetal weight]/days) and ∆childwt ([weight minus birthweight]/years) were divided into quartiles and comparisons made examining CM differences between ∆fetalwt and ∆childwt quartiles. Differentially expressed metabolites (DEMs) and genes (DEGs) were established using MetaboAnalyst and EdgeR. Gene set enrichment analysis (GSEA) identified associated pathways. As an alternative approach, we used k-means clustering to separate participants into groups based solely on their transcriptome, with GSEA on DEGs.

Results: 69% (56/81) had ∆fetalwt <0, consistent with FGR, but only 12% (10/81) were SGA. SBP was higher and HDL lower in ∆fetalwt Q1 (most negative) vs Q4. SBP, BMI SDS, AC, MUAC, AI and %fat were higher in ∆childwt Q4 (most positive) vs Q1 (all P<0.05). There was a trend towards higher insulin (Q4 mean 29.9pmol/l (SD 13.1) vs Q1 20.5 (10.5), P=0.085). Ornithine was a DEM for both ∆fetalwt and ∆childwt. DEGs between ∆childwt quartiles highlighted a pathway including ANXA3, encoding annexin A3 which cleaves inositol-1,2-cyclic phosphate, and ARG1, encoding arginase which catalyses arginine to ornithine hydrolysis. K-means clustering defined two groups, who had a difference in SBP (median 111mmHg (range 101-134), n=7 vs 102 (89-122), n=24, P=0.009). The most significant DEG was LATS1, encoding an enzyme regulating cell proliferation. GSEA identified GHRL, encoding a ghrelin and obestatin precursor.

Conclusions: CM markers were related to low ∆fetalwt and high ∆childwt, with a less favourable CM profile after pregnancies with suboptimal fetal growth but not necessarily SGA at birth. The arginine-nitric-oxide and phosphatidyl-inositol pathways were associated with adverse growth patterns. Analysis dividing the participants solely on transcriptomics identified a gene related to appetite regulation.