Submit a Letter to the Editor
Abstract
BACKGROUND. The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and random forest analysis. METHODS. Prepubertal treatment-naive children with GHD (n = 98) were enrolled from the PREDICT study, and controls (n = 26) were acquired from online data sets. Whole blood gene expression was correlated with peak growth hormone (GH) using rank regression and a random forest algorithm tested for prediction of the presence of GHD and in classification of GHD as severe (peak GH <4 μg/l) and nonsevere (peak ≥4 μg/l). Performance was assessed using area under the receiver operating characteristic curve (AUC-ROC). RESULTS. Rank regression identified 347 probe sets in which gene expression correlated with peak GH concentrations (r = ± 0.28, P < 0.01). These 347 probe sets yielded an AUC-ROC of 0.95 for prediction of GHD status versus controls and an AUC-ROC of 0.93 for prediction of GHD severity. CONCLUSION. This study demonstrates highly accurate diagnosis and disease classification for GHD using a combination of transcriptomics and random forest analysis. TRIAL REGISTRATION. NCT00256126 and NCT00699855. FUNDING. Merck and the National Institute for Health Research (CL-2012-06-005).
Authors
Philip G. Murray, Adam Stevens, Chiara De Leonibus, Ekaterina Koledova, Pierre Chatelain, Peter E. Clayton
Guidelines: The Editorial Board will only consider letters that we deem relevant and of interest to our readers. We will not post data that have not been subjected to peer review, nor will we post letters that are essentially a reiteration of another letter. We reserve the right to edit any letter for length, content, and clarity. Authors will be notified by e-mail if their letters were accepted. No appeals will be considered.
Specific requirements: All letters must be 400 words or fewer. You may enter the letter as plain text or HTML. The author's name and e-mail address are required, and will be posted with the letter. All possible conflicts of interest must be noted, even if they are not posted. If you wish to include a figure (keep in mind that non-peer-reviewed data will not be posted), please contact the editors directly at editors@the-jci.org.
