Cargando…
Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine
The clinical characteristics and prognoses of acromegaly vary among patients. Assessment of current and novel predictors can lead to multilevel categorization of patients, allowing integration into new clinical guidelines and a reduction in the increased morbidity and mortality associated with acrom...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Endocrine Society
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10613768/ https://www.ncbi.nlm.nih.gov/pubmed/37828709 http://dx.doi.org/10.3803/EnM.2023.1820 |
_version_ | 1785128900866605056 |
---|---|
author | Kim, Kyungwon Ku, Cheol Ryong Lee, Eun Jig |
author_facet | Kim, Kyungwon Ku, Cheol Ryong Lee, Eun Jig |
author_sort | Kim, Kyungwon |
collection | PubMed |
description | The clinical characteristics and prognoses of acromegaly vary among patients. Assessment of current and novel predictors can lead to multilevel categorization of patients, allowing integration into new clinical guidelines and a reduction in the increased morbidity and mortality associated with acromegaly. Despite advances in the diagnosis and treatment of acromegaly, its pathophysiology remains unclear. Recent advancements in multiomics technologies, including genomics, transcriptomics, proteomics, metabolomics, and radiomics, have offered new opportunities to unravel the complex pathophysiology of acromegaly. This review comprehensively explores the emerging role of multiomics approaches in elucidating the molecular landscape of acromegaly. We discuss the potential implications of multiomics data integration in the development of novel diagnostic tools, identification of therapeutic targets, and the prospects of precision medicine in acromegaly management. By integrating diverse omics datasets, these approaches can provide valuable insights into disease mechanisms, facilitate the identification of diagnostic biomarkers, and identify potential therapeutic targets for precision medicine in the management of acromegaly. |
format | Online Article Text |
id | pubmed-10613768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Korean Endocrine Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-106137682023-10-31 Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine Kim, Kyungwon Ku, Cheol Ryong Lee, Eun Jig Endocrinol Metab (Seoul) Songwon Lecture 2022 The clinical characteristics and prognoses of acromegaly vary among patients. Assessment of current and novel predictors can lead to multilevel categorization of patients, allowing integration into new clinical guidelines and a reduction in the increased morbidity and mortality associated with acromegaly. Despite advances in the diagnosis and treatment of acromegaly, its pathophysiology remains unclear. Recent advancements in multiomics technologies, including genomics, transcriptomics, proteomics, metabolomics, and radiomics, have offered new opportunities to unravel the complex pathophysiology of acromegaly. This review comprehensively explores the emerging role of multiomics approaches in elucidating the molecular landscape of acromegaly. We discuss the potential implications of multiomics data integration in the development of novel diagnostic tools, identification of therapeutic targets, and the prospects of precision medicine in acromegaly management. By integrating diverse omics datasets, these approaches can provide valuable insights into disease mechanisms, facilitate the identification of diagnostic biomarkers, and identify potential therapeutic targets for precision medicine in the management of acromegaly. Korean Endocrine Society 2023-10 2023-10-13 /pmc/articles/PMC10613768/ /pubmed/37828709 http://dx.doi.org/10.3803/EnM.2023.1820 Text en Copyright © 2023 Korean Endocrine Society https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Songwon Lecture 2022 Kim, Kyungwon Ku, Cheol Ryong Lee, Eun Jig Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine |
title | Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine |
title_full | Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine |
title_fullStr | Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine |
title_full_unstemmed | Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine |
title_short | Multiomics Approach to Acromegaly: Unveiling Translational Insights for Precision Medicine |
title_sort | multiomics approach to acromegaly: unveiling translational insights for precision medicine |
topic | Songwon Lecture 2022 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10613768/ https://www.ncbi.nlm.nih.gov/pubmed/37828709 http://dx.doi.org/10.3803/EnM.2023.1820 |
work_keys_str_mv | AT kimkyungwon multiomicsapproachtoacromegalyunveilingtranslationalinsightsforprecisionmedicine AT kucheolryong multiomicsapproachtoacromegalyunveilingtranslationalinsightsforprecisionmedicine AT leeeunjig multiomicsapproachtoacromegalyunveilingtranslationalinsightsforprecisionmedicine |