{"doi":"10.1210/clinem/dgad717","title":"Gene Expression Signatures Predict First-Year Response to Somapacitan Treatment in Children With Growth Hormone Deficiency","abstract":"<jats:title>Abstract</jats:title>\n               <jats:sec>\n                  <jats:title>Context</jats:title>\n                  <jats:p>The pretreatment blood transcriptome predicts growth response to daily growth hormone (GH) therapy with high accuracy.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Objective</jats:title>\n                  <jats:p>Investigate response prediction using pretreatment transcriptome in children with GH deficiency (GHD) treated with once-weekly somapacitan, a novel long-acting GH.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Methods</jats:title>\n                  <jats:p>REAL4 is a randomized, multinational, open-label, active-controlled parallel group phase 3 trial, comprising a 52-week main phase and an ongoing 3-year safety extension (NCT03811535). A total of 128/200 treatment-naïve prepubertal children with GHD consented to baseline blood transcriptome profiling. They were randomized 2:1 to subcutaneous somapacitan (0.16 mg/kg/week) or daily GH (0.034 mg/kg/day). Differential RNA-seq analysis and machine learning were used to predict therapy response.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>121/128 samples passed quality control. Children treated with somapacitan (n = 76) or daily GH (n = 45) were categorized based on fastest and slowest growing quartiles at week 52. Prediction of height velocity (HV; cm/year) was excellent for both treatments (out of bag [OOB] area under curve [AUC]: 0.98-0.99; validation AUC: 0.83-0.84), as was prediction of secondary markers of growth response: HV standard deviation score (SDS) (0.99-1.0; 0.75-0.78), change from baseline height SDS (ΔHSDS) (0.98-1.0; 0.61-0.75), and change from baseline insulin-like growth factor-I SDS (ΔIGF-I SDS) (0.96-1.0; 0.85-0.88). Genes previously identified as predictive of GH therapy response were consistently better at predicting the fastest growers in both treatments in this study (OOB AUC: 0.93-0.97) than the slowest (0.67-0.85).</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion</jats:title>\n                  <jats:p>Pretreatment transcriptome predicts first-year growth response in somapacitan-treated children with GHD. A common set of genes can predict the treatment response to both once-weekly somapacitan and conventional daily GH. This approach could potentially be developed into a clinically applicable pretreatment test to improve clinical management.</jats:p>\n               </jats:sec>","journal":"The Journal of Clinical Endocrinology &amp; Metabolism","year":2024,"id":600392,"datarank":0.31191623125197543,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"self_citation_contribution":0.31191623125197543,"citation_network_contribution":0.0,"self_endowment_contribution":0.31191623125197543,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1539228,"name":"Peter Clayton","orcid":"0000-0003-1225-4537","position":1,"is_corresponding":false},{"id":1539229,"name":"Michael Højby","orcid":null,"position":2,"is_corresponding":false},{"id":1005684,"name":"Philip Murray","orcid":"0000-0002-1480-1576","position":3,"is_corresponding":false},{"id":1539230,"name":"Adam Stevens","orcid":"0000-0002-1950-7325","position":4,"is_corresponding":false},{"id":1539227,"name":"Terence Garner","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Gene Expression Signatures Predict First-Year Response to Somapacitan Treatment in Children With Growth Hormone Deficiency","abstract":"<jats:title>Abstract</jats:title>\n               <jats:sec>\n                  <jats:title>Context</jats:title>\n                  <jats:p>The pretreatment blood transcriptome predicts growth response to daily growth hormone (GH) therapy with high accuracy.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Objective</jats:title>\n                  <jats:p>Investigate response prediction using pretreatment transcriptome in children with GH deficiency (GHD) treated with once-weekly somapacitan, a novel long-acting GH.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Methods</jats:title>\n                  <jats:p>REAL4 is a randomized, multinational, open-label, active-controlled parallel group phase 3 trial, comprising a 52-week main phase and an ongoing 3-year safety extension (NCT03811535). A total of 128/200 treatment-naïve prepubertal children with GHD consented to baseline blood transcriptome profiling. They were randomized 2:1 to subcutaneous somapacitan (0.16 mg/kg/week) or daily GH (0.034 mg/kg/day). Differential RNA-seq analysis and machine learning were used to predict therapy response.</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>121/128 samples passed quality control. Children treated with somapacitan (n = 76) or daily GH (n = 45) were categorized based on fastest and slowest growing quartiles at week 52. Prediction of height velocity (HV; cm/year) was excellent for both treatments (out of bag [OOB] area under curve [AUC]: 0.98-0.99; validation AUC: 0.83-0.84), as was prediction of secondary markers of growth response: HV standard deviation score (SDS) (0.99-1.0; 0.75-0.78), change from baseline height SDS (ΔHSDS) (0.98-1.0; 0.61-0.75), and change from baseline insulin-like growth factor-I SDS (ΔIGF-I SDS) (0.96-1.0; 0.85-0.88). Genes previously identified as predictive of GH therapy response were consistently better at predicting the fastest growers in both treatments in this study (OOB AUC: 0.93-0.97) than the slowest (0.67-0.85).</jats:p>\n               </jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion</jats:title>\n                  <jats:p>Pretreatment transcriptome predicts first-year growth response in somapacitan-treated children with GHD. A common set of genes can predict the treatment response to both once-weekly somapacitan and conventional daily GH. This approach could potentially be developed into a clinically applicable pretreatment test to improve clinical management.</jats:p>\n               </jats:sec>","is_dataset_classified":null,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"38066644","pmcid":"PMC11031233","openalex_id":"https://openalex.org/W4389514299","authors":[],"funders":[{"funder_name":"Novo Nordisk A/S","grant_id":"","title":null},{"funder_name":"Novo Nordisk A/S","grant_id":"","title":null}],"total_grants":2,"fwci":1.176,"citation_percentile":0.81584821,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":1},{"year":2025,"count":3},{"year":2026,"count":2}],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://academic.oup.com/jcem/advance-article-pdf/doi/10.1210/clinem/dgad717/54128246/dgad717.pdf","host_type":"journal"},{"url":"https://academic.oup.com/jcem/advance-article-pdf/doi/10.1210/clinem/dgad717/54128246/dgad717.pdf","host_type":"publisher"},{"url":"https://academic.oup.com/jcem/advance-article-pdf/doi/10.1210/clinem/dgad717/54760030/dgad717.pdf","host_type":"publisher"},{"url":"https://academic.oup.com/jcem/article-pdf/109/5/1214/57285724/dgad717.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1210/clinem/dgad717","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/38066644","host_type":"repository"},{"url":"https://research.manchester.ac.uk/en/publications/b9ef4da4-6cba-40c5-9694-cd8b63673368","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11031233","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC11031233","host_type":"Europe_PMC"}],"fields_of_study":["Growth Hormone and Insulin-like Growth Factors","Genetic Syndromes and Imprinting","TGF-β signaling in diseases","Child","Humans","Body Height","Dwarfism, Pituitary","Growth Hormone","Histidine","Human Growth Hormone","Insulin-Like Growth Factor I","Mannitol","Phenol","Transcriptome"],"mesh_terms":["Body Height","Child","Dwarfism, Pituitary","Histidine","Humans","Insulin-Like Growth Factor I","Mannitol","Growth Hormone","Human Growth Hormone","Phenol","Transcriptome"],"keywords":["Medicine","Internal medicine","Transcriptome","Quartile","Randomized controlled trial","Gastroenterology","Endocrinology","Gene expression","Confidence interval","Biology","Gene","Biochemistry","Growth Hormone Deficiency","Predictive Markers","Long-acting Growth Hormone","Somapacitan","And Rna Sequencing","Pretreatment Blood Transcriptome"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"nct"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-29T13:03:56.273815Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}