Gene expression signatures predict response to therapy with growth hormone
Adam Stevens, Philip Murray, Chiara De Leonibus, Terence Garner, Ekaterina Koledova, Geoffrey Ambler, Klaus Kapelari, Gerhard Binder, Mohamad Maghnie, Stefano Zucchini, Elena Bashnina, Julia Skorodok, Diego Yeste, Alicia Belgorosky, Juan-Pedro Lopez Siguero, R. Coutant, Eirik Vangsøy-Hansen, Lars Hagenäs, Jovanna Dahlgren, Cheri Deal, Pierre Chatelain, Peter Clayton
Abstract
Recombinant human growth hormone (r-hGH) is used as a therapeutic agent for disorders of growth including growth hormone deficiency (GHD) and Turner syndrome (TS). Treatment is costly and current methods to model response are inexact. GHD (n = 71) and TS patients (n = 43) were recruited to study response to r-hGH over 5 years. Analysis was performed using 1219 genetic markers and baseline (pre-treatment) blood transcriptome. Random forest was used to determine predictive value of transcriptomic data associated with growth response. No genetic marker passed the stringency criteria for prediction. However, we identified an identical set of genes in both GHD and TS whose expression could be used to classify therapeutic response to r-hGH with a high accuracy (AUC > 0.9). Combining transcriptomic markers with clinical phenotype was shown to significantly reduce predictive error. This work could be translated into a single genomic test linked to a prediction algorithm to improve clinical management. Trial registration numbers: NCT00256126 and NCT00699855.