ESPE2015 Poster Category 2 GH & IGF (40 abstracts)
aFaculty of Medical and Human Sciences, Institute of Human Development, Royal Manchester Childrens Hospital, University of Manchester and Manchester Academic Health Science Centre, Central Manchester, Manchester, UK; bMerck Serono, Darmstadt, Germany; cDepartment Pediatrie, Hôpital Mère-Enfant, Université Claude Bernard, Lyon, France
Background: GH deficiency (GHD) is classically defined on the basis of a cut-off applied to the peak GH level during stimulation tests; a process with recognised limitations. Identifying the functional role of genes whose expression is associated with pGH may help with our understanding and classification of GHD.
Objective and hypotheses: Identify patterns of gene expression (GE) related to pGH and to describe the function, and regulation of these genes.
Method: Pre-pubertal children with GHD (n=98) were enrolled from the PREDICT study (NCT00256126). All children enrolled had two GH stimulation tests both with pGH levels <10 μg/l. Whole blood GE was determined prior to GH treatment using Affymetrix U133v2 microarrays. GE was correlated with pGH using rank regression (gender, ethnicity, age, and BMI as co-variates). Network models were generated (Biogrid/Cytoscape) and the hierarchy of gene modules determined (Moduland); upstream activity in the network model was assessed using causal network analysis (Ingenuity Pathway Analysis).
Results: Rank regression identified 347 genes that were correlated with pGH: 188 positively and 159 negatively (R>±0.28, P<0.01). Hierarchical clustering identified five distinct clusters of GE (two clusters positively correlated with pGH and three negatively correlated). For the positively correlated GE clusters one cluster associated with network modules related to cell cycle and the second with chromatin remodelling and circadian clock (P<0.01). For the negatively correlated GE clusters two associated with network modules related to circadian clock, DNA replication and WNT signalling while the third associated with apoptosis (P<0.01). Upstream regulators of these modules were PIK3R3 (circadian clock), SIRT2 (growth factor signalling), and APC2 (WNT signalling) (P<7.7×10−3).
Conclusion: GE profiling identified a genomic signature related to pGH levels functionally linked to circadian clock and growth factor signalling and regulated by PIK3R3, SIRT2, and APC2.