Unmasking primary aldosteronism: Transforming disease management with advanced steroid profiling.

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Tác giả: Tashi Paljor, Ling Qiu, SongLin Yu, Jian Zhong

Ngôn ngữ: eng

Ký hiệu phân loại: 627.12 Rivers and streams

Thông tin xuất bản: Netherlands : Clinica chimica acta; international journal of clinical chemistry , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 179161

Primary aldosteronism (PA) is traditionally thought to result from the overproduction of aldosterone which is unregulated by the renin-angiotensin system. It leads to a significantly increased risk of cardiovascular and metabolic complications as compared to primary hypertension. However, approximately one-third of patients diagnosed with PA according to the traditional guidelines have been found to exhibit low aldosterone levels and other steroid hormones may also play a potentially critical role in PA development. Early diagnosis of PA remains challenging due to low screening rates and the complex diagnostic procedures. The need for invasive adrenal vein sampling for PA subtyping also leads to a dilemma in therapeutic strategy selection. With advances in techniques, an increasing number of steroid hormones have been discovered to be associated with PA, potentially optimizing the PA diagnostic procedures. Herein, we review the cutting-edge advances in steroid hormones, including aberrant hormone synthesis and metabolism related to the pathophysiological development of PA, quantitative assays, and potential clinical value. Mass spectrometry provides a robust technical foundation for the simultaneous profiling of a panel of steroid hormones. Steroid hormone profiling combined with machine learning algorithms holds great research promise for facilitating early diagnosis and minimally invasive subtyping of PA. Thus, current progress and future expectations in combining steroid hormones with advanced technologies for early disease diagnosis and management are also reviewed. Research Agenda. 1) Identify changes in steroid hormones and the underlying biochemical mechanisms associated with PA. 2) Investigate the role of advanced mass spectrometry techniques in steroid hormone profiling. 3) Discuss current advances and future expectations in combining machine learning algorithms with MS-based steroid hormone profiling for PA's systematic and practical management.
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