Frontiers in endocrinology · 2025
Serum microRNAs as peripheral markers of primary aldosteronism.
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Makhnov Nikita, Axling Fredrik, Barazeghi Elham, Stålberg Peter, Åkerström Tobias, Hellman Per
Аннотация
BACKGROUND: Primary aldosteronism (PA) is the principal cause of secondary hypertension; it leads to significantly elevated cardiovascular morbidity and mortality, but only a fraction of its cases ever get detected, partially due to diagnostic procedures that are difficult to perform and to interpret. More straightforward diagnostic methods are needed. Lateralized, or unilateral PA (uPA), is best treated by surgery. Bilateral PA (bPA) is treated medically.
AIM: The aim of our study was to explore microRNA (miRNA) in peripheral blood as markers of PA, uPA and bPA.
METHODS: In groups of subjects with primary hypertension (HT, n = 11), bPA (n = 12), and uPA (n = 16), peripheral serum was used for isolation of total RNA, library preparation, and NGS sequencing to achieve a comparative analysis of miRNA expression. Five-fold cross-validation support vector machine learning (ML) models were employed to search for miRNA that could be used as markers of PA and its forms.
RESULTS: In our cohort of patients, the discovered combinations of miRNAs could, with a high level of accuracy, sensitivity, and specificity, characterize the difference between HT and PA, as well as between a combined group of HT + bPA vs. uPA. The differentiating parameters were moderately good for comparison of bPA vs. uPA.
CONCLUSION: Within our patient cohort, and using ML, the study identified distinctly different miRNA profiles between HT and PA, as well as between bPA and uPA. Further validation studies may lead to the emergence of a new tool for clinical diagnostics of PA.
AIM: The aim of our study was to explore microRNA (miRNA) in peripheral blood as markers of PA, uPA and bPA.
METHODS: In groups of subjects with primary hypertension (HT, n = 11), bPA (n = 12), and uPA (n = 16), peripheral serum was used for isolation of total RNA, library preparation, and NGS sequencing to achieve a comparative analysis of miRNA expression. Five-fold cross-validation support vector machine learning (ML) models were employed to search for miRNA that could be used as markers of PA and its forms.
RESULTS: In our cohort of patients, the discovered combinations of miRNAs could, with a high level of accuracy, sensitivity, and specificity, characterize the difference between HT and PA, as well as between a combined group of HT + bPA vs. uPA. The differentiating parameters were moderately good for comparison of bPA vs. uPA.
CONCLUSION: Within our patient cohort, and using ML, the study identified distinctly different miRNA profiles between HT and PA, as well as between bPA and uPA. Further validation studies may lead to the emergence of a new tool for clinical diagnostics of PA.