Biomarkers for subtype stratification in primary aldosteronism: current and future perspectives.

Area of Science:

• Endocrinology
• Hypertension Research
• Diagnostic Imaging

Background:

• Primary aldosteronism is the leading endocrine cause of secondary hypertension.
• Accurate subtype classification (lateralized vs. bilateral) is essential for guiding treatment decisions, such as adrenalectomy or medical management.
• Current diagnostic methods, including imaging and adrenal vein sampling, have limitations in sensitivity, standardization, and accessibility.

Purpose of the Study:

• To review current evidence and explore future directions for biomarker-driven stratification in primary aldosteronism.
• To highlight the challenges in differentiating primary aldosteronism subtypes.
• To assess the potential of novel diagnostic approaches.

Main Methods:

• Review of current literature on diagnostic modalities for primary aldosteronism.
• Discussion of limitations of conventional imaging and adrenal vein sampling.
• Exploration of emerging non-invasive biomarkers (steroid profiling, circulating proteins, microRNAs) and machine learning approaches.

Main Results:

• Conventional imaging lacks sensitivity and can misclassify lateralization.
• Adrenal vein sampling, while the gold standard, is technically complex and lacks standardization.
• Steroid profiling shows encouraging diagnostic accuracy, and machine learning offers integrative analysis of multidimensional data.

Conclusions:

• Non-invasive biomarkers and advanced computational methods like machine learning hold significant potential for improving primary aldosteronism subtype differentiation.
• Integration of clinical data, imaging, and comprehensive biomarker profiles can refine lateralization predictions.
• Overcoming implementation barriers, including analytical variability and economic factors, is crucial for clinical adoption.