Endocrinology, Institute of Endocrine Research, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.
Endocrinol Metab (Seoul). 2023 Oct;38(5):463-471. doi: 10.3803/EnM.2023.1820. Epub 2023 Oct 13.
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.
肢端肥大症患者的临床特征和预后存在差异。评估当前和新的预测因子可以对患者进行多层次分类，从而将其纳入新的临床指南，并降低与肢端肥大症相关的发病率和死亡率的增加。尽管肢端肥大症的诊断和治疗取得了进展，但它的病理生理学仍不清楚。多组学技术（包括基因组学、转录组学、蛋白质组学、代谢组学和放射组学）的最新进展为揭示肢端肥大症的复杂病理生理学提供了新的机会。这篇综述全面探讨了多组学方法在阐明肢端肥大症分子图谱中的新兴作用。我们讨论了多组学数据集成在开发新的诊断工具、确定治疗靶点以及肢端肥大症管理中精准医学的前景中的潜在意义。通过整合不同的组学数据集，这些方法可以为疾病机制提供有价值的见解，有助于识别诊断生物标志物，并确定肢端肥大症精准医学管理的潜在治疗靶点。
