ESPE Abstracts (2022) 95 FC10.2

ESPE2022 Free Communications GH and IGFs (6 abstracts)

The first-year growth response to once-weekly growth hormone (GH) treatment can be predicted from the pre-treatment blood transcriptome in children with GH deficiency (GHD)

Terence Garner 1 , Peter Clayton 1,2 , Philip Murray 1,2 , Ekaterine Bagci 3 , Michael Højby 3 & Adam Stevens 1

1Division of Developmental Biology and Medicine, Faculty of Biology, Medicine and Health, University of Manchester and Manchester Academic Health Science Centre, Manchester, United Kingdom; 2Department of Paediatric Endocrinology, Royal Manchester Children’s Hospital, Manchester, United Kingdom; 3Novo Nordisk, Clinical Drug Development, Søborg, Denmark

Growth response to daily GH treatment can be predicted using pre-treatment gene expression profiles.1 Once-weekly GH treatment potentially reduces the burden of daily injections2 and thus may be a major advancement in care for patients with GHD, vs standard, daily GH treatment. Here we investigate the prediction of first-year growth response based on pre-treatment blood transcriptome in children with GHD undergoing treatment with daily or once-weekly GH. Two hundred GH-treatment-naïve prepubertal children with a confirmed diagnosis of GHD and no prior exposure to GH therapy were enrolled into a randomised, multinational, multicentre, open-labelled, and active-controlled parallel-group phase 3 trial, REAL 4. One-hundred-and-twenty-eight of these consented to participate in a baseline blood transcriptome profile. These children with GHD were treated with daily GH (n=47) or once-weekly somapacitan (n=81) over 52 weeks. Participants were categorised based on their response to GH treatment. The participants within the upper quartile of annualised HV (cm/year) were identified as good responders; the lower quartile as poor responders. Differential expression was assessed between the target quartile and the remaining three quartiles to identify the top 100 differentially expressed genes (DEGs) by adjusted P-value. Classes were balanced using a synthetic minority oversampling technique (SMOTE) and Boruta, a feature selection algorithm that models background noise, was used to refine gene lists. Random forest was performed using these genes and “out of box” (OOB), area under the curve (AUC), and OOB error rate (ER), measures of predictive accuracy and robustness respectively, were calculated. All analyses were performed in R 4.4.1. There was no difference in baseline clinical phenotype or annualised height velocity between daily GH and once-weekly somapacitan. Prediction of growth response using the baseline (Pre-treatment) blood transcriptome was excellent for both treatments (AUC range: 0.91–0.98) but prediction was consistently more robust in the identification of the good (ER: 7.0–11.5%) than the poor responders (ER:13.2–15.8%). Gene transcripts previously identified as predictive of growth response in daily GH treatment1 were demonstrated to have predictive value in both daily and once-weekly GH treatment (AUC range: 0.84–0.97, ER <22%). This is the first demonstration of the use of pre-treatment blood transcriptome to predict first-year growth response to a novel once-weekly GH treatment. This study presents an independent validation of previous observations of the prediction of first-year response to daily GH treatment.

1. Stevens et al. Pharmacogenomics J doi: 10.1038/s41397-021-00237-5 (2021).

2. Christiansen et al. Eur J Endocrinol doi: 10.1530/EJE-16-0111 (2016).

Volume 95

60th Annual ESPE (ESPE 2022)

Rome, Italy
15 Sep 2022 - 17 Sep 2022

European Society for Paediatric Endocrinology 

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