3-M syndrome is a primordial growth disorder caused by mutations in CUL7, OBSL1 or CCDC8. 3-M patients typically have a modest response to GH treatment, but the mechanism is unknown. Our aim was to screen 13 clinically identified 3-M families for mutations, define the status of the GH-IGF axis in 3-M children and using fibroblast cell lines assess signalling responses to GH or IGF1. Eleven CUL7, three OBSL1 and one CCDC8 mutations in nine, three and one families respectively were identified, those with CUL7 mutations being significantly shorter than those with OBSL1 or CCDC8 mutations. The majority of 3-M patients tested had normal peak serum GH and normal/low IGF1. While the generation of IGF binding proteins by 3-M cells was dysregulated, activation of STAT5b and MAPK in response to GH was normal in CUL7

Small for gestational age (SGA) children exhibiting catch-up (CU) growth have a greater risk of cardiometabolic diseases in later life compared with non-catch-up (NCU) SGA children. The aim of this study was to establish differences in metabolism and gene expression profiles between CU and NCU at age 4-9 years. CU children (n=22) had greater height, weight and body mass index standard deviation scores along with insulin-like growth factor-I (IGF-I) and fasting glucose levels but lower adiponectin values than NCU children (n=11; all P<0.05). Metabolic profiling demonstrated a fourfold decrease of urine myo-inositol in CU compared with NCU (P<0.05). There were 1558 genes differentially expressed in peripheral blood mononuclear cells between the groups (P<0.05). Integrated analysis of data identified myo-inositol related to gene clusters associated with an increase in insulin, growth factor and IGF-I signalling in CU children (P<0.05). Metabolic and transcriptomic profiles in CU SGA children showed changes that may relate to cardiometabolic risk.

The majority of children born SGA exhibit catch-up (CU) growth in the early years of life. However, 10% do not catch-up (NCU) [∼2000 per annum in the UK) and become eligible for GH treatment at age 4 years. All these SGA babies, in particular those with CU, have an increased risk of vascular and metabolic disease in later life. A marker of future growth pattern would allow early lifestyle intervention for those destined to CU and earlier GH treatment for the NCU. Metabolomics can be used to characterise and quantify small metabolites and metabolic intermediates in blood and urine. We have therefore compared metabolomic profiles in prepubertal children born SGA who have exhibited either CU or NCU growth. Samples were taken from 23 children at mean age of 5.7 ± 1.9 years in NCU and 6.2 ± 1.1 years in CU. 16 blood samples (7 NCU, 9 CU) and 19 urines (10 NCU, 9 CU) were analysed. Both groups had comparable birth weight SD scores: NCU −2.6 ± 1, CU −2.5 ± 0.4. The CU group had a current height SD score of −0.4 ± 1.1 versus −3.2 ± 0.9 in the NCU group (p<0.001). Samples were analysed by mass spectrometry coupled to either gas or liquid chromatography. In urine, myo-inositol (involved in insulin and IGF signalling) was 5-fold lower in CU compared to NCU (p=0.03), while uric acid and carnitine were 2-fold higher (p=0.007 & p=0.03 respectively). In serum, 3 amino acids, asparagine (p=0.03), glutamine (p=0.03) and serine (p=0.04), were 2-fold higher in CU compared to NCU. CU had significantly higher levels of bile acids, vitamin D metabolites and glycerophosphotidylcholines and decreased levels of sphingolipids compared to NCU. Conclusion There are significant differences in mid-childhood in metabolic profiles of CU versus NCU children born SGA, with such discrepancies potentially affecting growth. We plan to undertake metabolomic studies in the first year of life prior to CU growth occurring to define early biomarkers of CU versus NCU growth.