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Despite advances, conventional subtype classification remains challenging. Cross-sectional imaging has limited sensitivity and may misclassify lateralisation due to discordance between anatomical findings and functional aldosterone secretion. Although adrenal vein sampling remains the gold standard for subtype differentiation, its technical complexity, cost, and lack of standardised protocols limit widespread implementation and contribute to inconsistent diagnostic outcomes across centres. The advent of molecular imaging tracers exemplifies the shift towards non-invasive diagnostics; however, their routine clinical adoption is restricted by limited availability, concerns regarding specificity, and lack of harmonisation. Circulating and urinary biomarkers remain promising non-invasive alternatives. Advances in steroid profiling via liquid chromatography\u2013mass spectrometry-based detection of hybrid steroids or steroid panels demonstrate encouraging diagnostic accuracy. While these biomarker approaches may assist subtype differentiation, anatomical localisation for surgical decision-making ultimately requires concordant imaging. Machine learning-driven approaches offer a promising solution by integratively analysing multidimensional datasets, including clinical features, imaging findings, and comprehensive biomarker profiles such as steroid profiles, circulating proteins, and microRNAs, to refine lateralisation predictions and overcome the limitations of individual diagnostic modalities. Nonetheless, implementation of these innovations into clinical practice remains hindered by analytical variability, insufficient population-specific validation, and economic barriers, especially in resource-limited settings. This review summarises current evidence and explores future directions for biomarker-driven stratification in primary aldosteronism.<\/jats:p>","DOI":"10.1093\/ejendo\/lvaf218","type":"journal-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T11:50:44Z","timestamp":1761133844000},"page":"R51-R64","source":"Crossref","is-referenced-by-count":6,"title":["Biomarkers for subtype stratification in primary aldosteronism: current and future perspectives"],"prefix":"10.1093","volume":"193","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2388-6444","authenticated-orcid":false,"given":"Tracy Ann","family":"Williams","sequence":"first","affiliation":[{"name":"Medizinische Klinik und Poliklinik IV, Klinikum der Universit\u00e4t M\u00fcnchen, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen , 80336 Munich ,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7304-2557","authenticated-orcid":false,"given":"Georgiana","family":"Constantinescu","sequence":"additional","affiliation":[{"name":"Department of Medicine III, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universit\u00e4t Dresden , 01307 Dresden ,","place":["Germany"]},{"name":"Department of Endocrinology, Grigore T Popa University of Medicine and Pharmacy , Ia\u0219i 700115 ,","place":["Romania"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0772-1604","authenticated-orcid":false,"given":"Christina","family":"Pamporaki","sequence":"additional","affiliation":[{"name":"Department of Medicine III, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universit\u00e4t Dresden , 01307 Dresden 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