Faculty of Biology, Medicine and Health, Division of Developmental Biology and Medicine, University of Manchester and Manchester Academic Health Science Centre, Royal Manchester Children's Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, UK.
Merck Healthcare KGaA, Darmstadt, Germany.
Pharmacogenomics J. 2021 Oct;21(5):594-607. doi: 10.1038/s41397-021-00237-5. Epub 2021 May 27.
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.
重组人生长激素(r-hGH)被用作治疗生长障碍的药物,包括生长激素缺乏症(GHD)和特纳综合征(TS)。治疗费用昂贵,目前模拟反应的方法并不准确。招募了 71 名 GHD 患者和 43 名 TS 患者,以研究 r-hGH 治疗 5 年的反应。使用 1219 个遗传标记物和基线(治疗前)血液转录组进行分析。随机森林用于确定与生长反应相关的转录组数据的预测价值。没有遗传标记物通过预测的严格标准。然而,我们在 GHD 和 TS 中都发现了一组相同的基因,其表达可以用于以高准确度(AUC>0.9)对 r-hGH 的治疗反应进行分类。将转录组标记物与临床表型相结合,可显著降低预测误差。这项工作可以转化为与预测算法相关的单一基因组测试,以改善临床管理。试验注册号:NCT00256126 和 NCT00699855。