METHODS: MiRNA profiling was conducted on plasma samples from 18 patients with primary aldosteronism taken during adrenal venous sampling on an Illumina MiSeq platform. Bioinformatics and machine learning identified 9 miRNAs for validation by reverse transcription real-time quantitative polymerase chain reaction. Validation was performed on a cohort consisting of 108 patients with known subdifferentiation. A 30-patient subset of the validation cohort involved both adrenal venous sampling and peripheral, the rest only peripheral samples. A neural network model was used for feature selection and comparison between adrenal venous sampling and peripheral samples, while a deep-learning model was used for classification.
RESULTS: Our model identified 10 miRNA combinations achieving >85% accuracy in distinguishing unilateral primary aldosteronism and bilateral adrenal hyperplasia on a 30-sample subset, while also confirming the suitability of peripheral samples for analysis. The best model, involving 6 miRNAs, achieved an area under curve of 87.1%. Deep learning resulted in 100% accuracy on the subset and 90.9% sensitivity and 81.8% specificity on all 108 samples, with an area under curve of 86.7%.
CONCLUSIONS: Machine learning analysis of circulating miRNAs offers a minimally invasive alternative for primary aldosteronism lateralization. Early identification of bilateral adrenal hyperplasia could expedite treatment initiation without the need for further localization, benefiting both patients and health care providers.
OBJECTIVE: The objective of the study was to delineate a process in human ZG, which may regulate both aldosterone production and cell turnover.
DESIGN: This study included a comparison of 20 pairs of ZG and zona fasciculata transcriptomes from adrenals adjacent to an APA (n = 13) or a pheochromocytoma (n = 7).
INTERVENTIONS: Interventions included an overexpression of the top ZG gene (LGR5) or stimulation by its ligand (R-spondin-3).
MAIN OUTCOME MEASURES: A transcriptome profile of ZG and zona fasciculata and aldosterone production, cell kinetic measurements, and Wnt signaling activity of LGR5 transfected or R-spondin-3-stimulated cells were measured.
RESULTS: LGR5 was the top gene up-regulated in ZG (25-fold). The gene for its cognate ligand R-spondin-3, RSPO3, was 5-fold up-regulated. In total, 18 genes associated with the Wnt pathway were greater than 2-fold up-regulated. ZG selectivity of LGR5, and its absence in most APAs, were confirmed by quantitative PCR and immunohistochemistry. Both R-spondin-3 stimulation and LGR5 transfection of human adrenal cells suppressed aldosterone production. There was reduced proliferation and increased apoptosis of transfected cells, and the noncanonical activator protein-1/Jun pathway was stimulated more than the canonical Wnt pathway (3-fold vs 1.3-fold). ZG of adrenal sections stained positive for apoptosis markers.
CONCLUSION: LGR5 is the most selectively expressed gene in human ZG and reduces aldosterone production and cell number. Such conditions may favor cells whose somatic mutation reverses aldosterone inhibition and cell loss.