Gene expression signatures predict response to therapy with growth hormone.

Child Female Gene Expression Profiling / methods Genetic Markers / genetics Growth Disorders / drug therapy Human Growth Hormone / deficiency Humans Male Prospective Studies Transcriptome / genetics Treatment Outcome Turner Syndrome / drug therapy

Journal

The pharmacogenomics journal
ISSN: 1473-1150
Titre abrégé: Pharmacogenomics J
Pays: United States
ID NLM: 101083949

Informations de publication

Date de publication:
10 2021
Historique:
received: 10 05 2020
accepted: 23 04 2021
revised: 17 03 2021
pubmed: 29 5 2021
medline: 11 3 2022
entrez: 28 5 2021
Statut: ppublish

Résumé

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.

Identifiants

DOI: 10.1038/s41397-021-00237-5 PMID: 34045667 PMC: PMC8455334
pubmed: 34045667
doi: 10.1038/s41397-021-00237-5
pii: 10.1038/s41397-021-00237-5
pmc: PMC8455334
doi:

Substances chimiques

Genetic Markers 0
Human Growth Hormone 12629-01-5

Banques de données

ClinicalTrials.gov
['NCT00699855', 'NCT00256126']

Types de publication

Clinical Trial, Phase IV Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

594-607

Subventions

Organisme : Medical Research Council
ID : MR/T024119/1
Pays : United Kingdom

Informations de copyright

© 2021. The Author(s).

Références

Excellence NIfHaC. Human growth hormone (somatropin) for the treatment of growth failure in children. 2010.
Ranke MB, Lindberg A, Brosz M, Kaspers S, Loftus J, Wollmann H, et al. Accurate long-term prediction of height during the first four years of growth hormone treatment in prepubertal children with growth hormone deficiency or Turner Syndrome. Horm Res Paediatr. 2012;78:8–17.
pubmed: 22832697 doi: 10.1159/000339468
Stevens A, De Leonibus C, Hanson D, Whatmore A, Murray P, Donn R, et al. Pediatric perspective on pharmacogenomics. Pharmacogenomics. 2013;14:1889–905.
pubmed: 24236488 doi: 10.2217/pgs.13.193
Stevens A, De Leonibus C, Whatmore A, Hanson D, Murray P, Chatelain P, et al. Pharmacogenomics related to growth disorders. Horm Res Paediatr. 2013;80:477–90.
pubmed: 24296333 doi: 10.1159/000355658
Stevens A, Murray P, Wojcik J, Raelson J, Koledova E, Chatelain P, et al. Validating genetic markers of response to recombinant human growth hormone in children with growth hormone deficiency and Turner syndrome: the PREDICT validation study. Eur J Endocrinol. 2016;175:633–43.
pubmed: 27651465 pmcid: 5097129 doi: 10.1530/EJE-16-0357
De Leonibus C, Chatelain P, Knight C, Clayton P, Stevens A. Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children. Pharmacogenomics J. 2016;16:540–50.
pubmed: 26503811 doi: 10.1038/tpj.2015.67
Clayton P, Chatelain P, Tato L, Yoo HW, Ambler GR, Belgorosky A, et al. A pharmacogenomic approach to the treatment of children with GH deficiency or Turner syndrome. Eur J Endocrinol. 2013;169:277–89.
pubmed: 23761422 pmcid: 3731924 doi: 10.1530/EJE-13-0069
Stevens A, Hanson D, Whatmore A, Destenaves B, Chatelain P, Clayton P. Human growth is associated with distinct patterns of gene expression in evolutionarily conserved networks. BMC Genom. 2013;14:547.
doi: 10.1186/1471-2164-14-547
Ranke MB, Lindberg A, Chatelain P, Wilton P, Cutfield W, Albertsson-Wikland K, et al. Derivation and validation of a mathematical model for predicting the response to exogenous recombinant human growth hormone (GH) in prepubertal children with idiopathic GH deficiency. KIGS International Board. Kabi Pharmacia International Growth Study. J Clin Endocrinol Metab. 1999;84:1174–83.
pubmed: 10199749 doi: 10.1210/jcem.84.4.5634
Ranke MB, Lindberg A, Chatelain P, Wilton P, Cutfield W, Albertsson-Wikland K, et al. Prediction of long-term response to recombinant human growth hormone in Turner syndrome: development and validation of mathematical models. KIGS International Board. Kabi International Growth Study. J Clin Endocrinol Metab. 2000;85:4212–8.
pubmed: 11095456 doi: 10.1210/jcem.85.11.6976
Ranke MB, Lindberg A, Chatelain P, Wilton P, Cutfield W, Albertsson-Wikland K, et al. Predicting the response to recombinant human growth hormone in Turner syndrome: KIGS models. KIGS International Board. Kabi International Growth Study. Acta Paediatr (Oslo, Nor: 1992) Suppl. 1999;88:122–5.
doi: 10.1111/j.1651-2227.1999.tb14420.x
Stevens A, Bonshek C, Whatmore A, Butcher I, Hanson D, De Leonibus C, et al. Insights into the pathophysiology of catch-up compared with non-catch-up growth in children born small for gestational age: an integrated analysis of metabolic and transcriptomic data. Pharmacogenomics J. 2014;14:376–84.
pubmed: 24614687 doi: 10.1038/tpj.2014.4
De Leonibus C, Chatelain P, Knight C, Clayton P, Stevens A. Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children. Pharmacogenomics J. 2015;16:540–50.
Gerber T, Willscher E, Loeffler-Wirth H, Hopp L, Schadendorf D, Schartl M, et al. Mapping heterogeneity in patient-derived melanoma cultures by single-cell RNA-seq. Oncotarget. 2017;8:846–62.
pubmed: 27903987 doi: 10.18632/oncotarget.13666
Grigoroiu M, Tagett R, Draghici S, Dima S, Nastase A, Florea R, et al. Gene-expression profiling in non-small cell lung cancer with invasion of mediastinal lymph nodes for prognosis evaluation. Cancer Genom Proteom. 2015;12:231–42.
Cavalli FMG, Remke M, Rampasek L, Peacock J, Shih DJH, Luu B, et al. Intertumoral heterogeneity within medulloblastoma subgroups. Cancer Cell. 2017;31:737–54.e6.
pubmed: 28609654 pmcid: 6163053 doi: 10.1016/j.ccell.2017.05.005
Bhutani M, Zhang Q, Friend R, Voorhees PM, Druhan LJ, Barlogie B, et al. Investigation of a gene signature to predict response to immunomodulatory derivatives for patients with multiple myeloma: an exploratory, retrospective study using microarray datasets from prospective clinical trials. Lancet Haematol. 2017;4:e443–e51.
pubmed: 28863804 doi: 10.1016/S2352-3026(17)30143-6
Kamel HFM, Al-Amodi H. Exploitation of gene expression and cancer biomarkers in paving the path to era of personalized medicine. Genom Proteom Bioinform. 2017;15:220–35.
doi: 10.1016/j.gpb.2016.11.005
Sävendahl L, Polak M, Backeljauw P, Blair J, Miller BS, Rohrer TR, et al. Treatment of children with GH in the United States and Europe: long-term follow-up from NordiNet
pubmed: 31305924 pmcid: 6812718 doi: 10.1210/jc.2019-00775
Shepherd S, Saraff V, Shaw N, Banerjee I, Patel L. Growth hormone prescribing patterns in the UK, 2013–2016. Arch Dis Child. 2019;104:583–7.
pubmed: 30567827 doi: 10.1136/archdischild-2018-316262
Stevens A, Clayton P, Tato L, Yoo HW, Rodriguez-Arnao MD, Skorodok J, et al. Pharmacogenomics of insulin-like growth factor-I generation during GH treatment in children with GH deficiency or Turner syndrome. Pharmacogenomics J. 2014;14:54–62.
pubmed: 23567489 doi: 10.1038/tpj.2013.14
Murray PG, Stevens A, De Leonibus C, Koledova E, Chatelain P, Clayton PE. Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency. JCI Insight. 2018;3:1–14.
Chatr-Aryamontri A, Breitkreutz BJ, Oughtred R, Boucher L, Heinicke S, Chen D, et al. The BioGRID interaction database: 2015 update. Nucleic Acids Res. 2015;43:D470–8.
pubmed: 25428363 doi: 10.1093/nar/gku1204
Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics. 2011;27:431–2.
pubmed: 21149340 doi: 10.1093/bioinformatics/btq675
Yu H, Kim PM, Sprecher E, Trifonov V, Gerstein M. The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol. 2007;3:e59.
pubmed: 17447836 pmcid: 1853125 doi: 10.1371/journal.pcbi.0030059
Sun J, Zhao Z. A comparative study of cancer proteins in the human protein-protein interaction network. BMC Genom. 2010;11:S5.
doi: 10.1186/1471-2164-11-S3-S5
Szalay-Beko M, Palotai R, Szappanos B, Kovacs IA, Papp B, Csermely P. ModuLand plug-in for Cytoscape: determination of hierarchical layers of overlapping network modules and community centrality. Bioinformatics. 2012;28:2202–4.
pubmed: 22718784 doi: 10.1093/bioinformatics/bts352
Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol. 2014;8:S11.
pubmed: 25521941 pmcid: 4290687 doi: 10.1186/1752-0509-8-S4-S11
Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43:D447–52.
pubmed: 25352553 doi: 10.1093/nar/gku1003
Kolarova J, Ammerpohl O, Gutwein J, Welzel M, Baus I, Riepe FG, et al. In vivo investigations of the effect of short- and long-term recombinant growth hormone treatment on DNA-methylation in humans. PLoS ONE. 2015;10:e0120463.
pubmed: 25785847 pmcid: 4364725 doi: 10.1371/journal.pone.0120463
RCoreTeam. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2016. https://www.R-project.org/ .
Jombart T, Devillard S, Balloux F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 2010;11:94.
pubmed: 20950446 pmcid: 2973851 doi: 10.1186/1471-2156-11-94
Rohart F, Gautier B, Singh A, Le, Cao KA. mixOmics: an R package for ‘omics feature selection and multiple data integration. PLoS Comput Biol. 2017;13:e1005752.
pubmed: 29099853 pmcid: 5687754 doi: 10.1371/journal.pcbi.1005752
Liaw A, Wiener M. Classification and regression by RandomForest. R News. 2002;2:18–22.
Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP. SMOTE: synthetic minority over-sampling technique. J Artif Intell Res. 2002;16:321–57.
doi: 10.1613/jair.953
Kursa MB, Rudnicki WR. Feature selection with the Boruta package. J Stat Softw. 2010;36:1–13.
doi: 10.18637/jss.v036.i11
Nilsson J, Fioretos T, Höglund M, Fontes M. Approximate geodesic distances reveal biologically relevant structures in microarray data. Bioinformatics. 2004;20:874–80.
pubmed: 14752004 doi: 10.1093/bioinformatics/btg496
Fontes M, Soneson C. The projection score–an evaluation criterion for variable subset selection in PCA visualization. BMC Bioinform. 2011;12:307.
doi: 10.1186/1471-2105-12-307
Ranke MB, Lindberg A. Predicting growth in response to growth hormone treatment. Growth Horm IGF Res: Off J Growth Horm Res Soc Int IGF Res Soc. 2009;19:1–11.
doi: 10.1016/j.ghir.2008.08.001
Tuo Y, An N, Zhang M. Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods. Mol Med Rep. 2018;17:4281–90.
pubmed: 29328377 pmcid: 5802200
Ranke MB, Wit JM. Growth hormone—past, present and future. Nat Rev Endocrinol. 2018;14:285–300.
pubmed: 29546874 doi: 10.1038/nrendo.2018.22
Wit JM, Ranke MB, Albertsson-Wikland K, Carrascosa A, Rosenfeld RG, Van Buuren S, et al. Personalized approach to growth hormone treatment: clinical use of growth prediction models. Horm Res Paediatr. 2013;79:257–70.
pubmed: 23735882 doi: 10.1159/000351025
Ranke MB, Schweizer R, Martin DD, Ehehalt S, Schwarze CP, Serra F, et al. Analyses from a centre of short- and long-term growth in Turner’s syndrome on standard growth hormone doses confirm growth prediction algorithms and show normal IGF-I levels. Horm Res Paediatr. 2012;77:214–21.
pubmed: 22433161 doi: 10.1159/000336806
Valsesia A, Chatelain P, Stevens A, Peterkova VA, Belgorosky A, Maghnie M, et al. GH deficiency status combined with GH receptor polymorphism affects response to GH in children. Eur J Endocrinol. 2015;173:777–89.
pubmed: 26340968 pmcid: 4623334 doi: 10.1530/EJE-15-0474
Dauber A, Meng Y, Audi L, Vedantam S, Weaver B, Carrascosa A, et al. A genome-wide pharmacogenetic study of growth hormone responsiveness. J Clin Endocrinol Metab. 2020;105:1–12.
Stevens A, De Leonibus C, Hanson D, Dowsey AW, Whatmore A, Meyer S, et al. Network analysis: a new approach to study endocrine disorders. J Mol Endocrinol. 2014;52:R79–93.
pubmed: 24085748 doi: 10.1530/JME-13-0112
Kovacs IA, Palotai R, Szalay MS, Csermely P. Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics. PLoS ONE. 2010;5:1–14.
Kolarova J, Ammerpohl O, Gutwein J, Welzel M, Baus I, Riepe FG, et al. In vivo investigations of the effect of short- and long-term recombinant growth hormone treatment on DNA-methylation in humans. PLoS ONE. 2015;10:e0120463.
pubmed: 25785847 pmcid: 4364725 doi: 10.1371/journal.pone.0120463
Chicco D. Ten quick tips for machine learning in computational biology. BioData Min. 2017;10:35.
pubmed: 29234465 pmcid: 5721660 doi: 10.1186/s13040-017-0155-3

Auteurs

Adam Stevens (A)

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.
ORCID: 0000-0002-1950-7325

Philip Murray (P)

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.

Chiara De Leonibus (C)

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.

Terence Garner (T)

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.

Ekaterina Koledova (E)

Merck Healthcare KGaA, Darmstadt, Germany.

Geoffrey Ambler (G)

The Children's Hospital, Westmead, Sydney, NSW, Australia.

Klaus Kapelari (K)

Medical University Innsbruck, Innsbruck, Austria.

Gerhard Binder (G)

University-Children's Hospital, Tuebingen, Germany.

Mohamad Maghnie (M)

IRCCS G. Gaslini, Genova, Italy.

Stefano Zucchini (S)

University of Bologna, Bologna, Italy.

Elena Bashnina (E)

North-Western State Medical University, Saint-Petersburg, Russian Federation.

Julia Skorodok (J)

Saint-Petersburg State Medical University, Saint-Petersburg, Russian Federation.

Diego Yeste (D)

Hospital Materno Infantil Vall d'Hebron, Barcelona, Spain.

Alicia Belgorosky (A)

Fundacion Hospital de Pediatria, Buenos Aires, Argentina.

Juan-Pedro Lopez Siguero (JL)

Children's Hospital Malaga, Malaga, Spain.

Regis Coutant (R)

University Hospital, Angers, France.

Eirik Vangsøy-Hansen (E)

Haukeland University Hospital, Bergen, Norway.

Lars Hagenäs (L)

Karolinska Hospital, Stockholm, Sweden.

Jovanna Dahlgren (J)

University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden.

Cheri Deal (C)

University of Montreal, Montreal, Quebec, Canada.

Pierre Chatelain (P)

Department Pediatrie, Hôpital Mère-Enfant-Université Claude Bernard, Lyon, France.

Peter Clayton (P)

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. peter.clayton@manchester.ac.uk.
ORCID: 0000-0003-1225-4537

Articles similaires

Comprehensive comparative analysis and development of molecular markers for Lasianthus species based on complete chloroplast genome sequences.

Yue Zhang, Meifang Song, Deying Tang et al.
1.00
Genome, Chloroplast Phylogeny Genetic Markers Base Composition High-Throughput Nucleotide Sequencing

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female

Evaluation of Low-Value Services Across Major Medicare Advantage Insurers and Traditional Medicare.

Ciara Duggan, Adam L Beckman, Ishani Ganguli et al.
1.00
Humans United States Aged Cross-Sectional Studies Medicare Part C

Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Enfant › Gene expression signatures predict response to...
questionsmedicales.fr › Techniques d'investigation › Techniques génétiques › Analyse de profil d'expression de gènes › Gene expression signatures predict response to...
questionsmedicales.fr › Phénomènes génétiques › Phénotype › Marqueurs génétiques › Gene expression signatures predict response to...
questionsmedicales.fr › États, signes et symptômes pathologiques › Processus pathologiques › Troubles de la croissance › Gene expression signatures predict response to...
questionsmedicales.fr › Acides aminés, peptides et protéines › Peptides › Hormones peptidiques › Hormones hypophysaires › Hormones antéhypophysaires › Hormone de croissance › Hormone de croissance humaine › Gene expression signatures predict response to...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Gene expression signatures predict response to...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études prospectives › Gene expression signatures predict response to...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Transcriptome › Gene expression signatures predict response to...
questionsmedicales.fr › Qualité, accès, évaluation des soins de santé › Qualité des soins de santé › Mécanismes d'évaluation des soins de santé › Évaluation des résultats et des processus en soins de santé › Évaluation de résultat (soins) › Résultat thérapeutique › Gene expression signatures predict response to...
questionsmedicales.fr › Maladies endocriniennes › Troubles gonadiques › Troubles du développement sexuel › Troubles du développement sexuel avec anomalie des gonosomes › Syndrome de Turner › Gene expression signatures predict response to...