72248 - Searching for biochemical peripheral markers of primary aldosteronism

Introduction Primary aldosteronism (PA) is common, clinically elusive, and causes considerable morbidity and mortality. The current praxis of diagnosing PA is cumbersome, invasive, and depends on arbitrary thresholds. Very few cases are clinically discovered; new diagnostic methods are needed. Method Hypertensive patients were evaluated for PA in accordance with the current guidelines. Those diagnosed with PA underwent adrenal vein catheterization and/or adrenocortical positron emission tomography. Three groups were included: primary hypertension (HT), lateralized or unilateral PA (uPA), and bilateral PA (bPA). Serum from 11 HT, 16 uPA, and 12 bPA patients was subjected to microRNA extraction and sequencing. Serum from 29 HT, 26 uPA, and 29 bPA was subjected to a proximity extension assay on a cardiometabolic 384 protein panel (Olink® Explore 384). Result Several differentially expressed miRNAs were identified between the groups HT versus PA, but also uPA versus bPA. To validate our results in an external cohort, a machine learning model was developed and applied to an earlier published primary aldosteronism dataset (Decmann et al., 2019). This model could discriminate uPA from bPA successfully in 83% of the cases. Numerous significantly different proteins were observed between the groups. Interestingly, one of the coagulation factors had a distinct elevated expression in both uPA and bPA versus HT, which could be confirmed by an ELISA assay. Validation using an external cohort is underway. Discussion Further studies of serum biomarkers as a tool for identifying PA and discriminating between uPA and bPA may aid in the diagnosis and subsequently improve the treatment outcomes of PA.