Bassiony, Mohamed

ABSTRACT Objective Data on bone health in patients with mild autonomous cortisol secretion (MACS) are limited and heterogenous. We sought to assess the prevalence of osteoporosis and symptomatic fragility fractures in patients with adrenal adenomas and hypercortisolism, and explore associations with the degree of cortisol excess and frailty. Design This multicenter cross ‐sectional study involved prospective enrollment of adults with nonfunctioning adrenal adenomas (NFA), MACS, Cushing syndrome (CS) and referent subjects without adrenal disorders during the study period (January 2019–September 2022). All participants completed a bone health questionnaire at enrollment and had dual‐energy X ‐ray absorptiometry bone mineral density assessment within 12‐months. Final analyses were adjusted for age, sex, body mass index, smoking status, alcohol use. Results Participants included 117 with NFA (median age 62 years, 80% women), 191 with MACS (median age 63 years, 74% women), 62 with CS (median age 50 years, 92% women), and 101 referent subjects (median age 59 years, 47% women). Both patients with CS (OR: 3.0, 95% CI: 1.1–8.3) and MACS (OR: 2.2, 95% CI: 1.9–4.9) had a higher prevalence of osteoporosis when compared to referents. Among patients with MACS, only those with post 1‐mg dexamethasone suppression test (post‐1mg‐DST) cortisol > 83 nmol/L had a higher prevalence of osteoporosis when compared to referents (OR: 3.2, 95% CI: 1.4–7.5) and NFA (OR: 2.2, 95% CI: 1.1–4.4). For clinical fragility fractures, only patients with CS showed an increased prevalence when compared to referents (OR: 6.1, 95% CI: 1.7–26.4) and NFA (OR: 3.8, 95% CI: 1.3–11.2). Prevalence of clinical fragility fractures was similar to referents in patients with MACS (OR: 1.8, 95% CI: 0.6–6.9) and NFA (OR: 1.5, 95% CI: 0.4–6.1), and was not associated with post‐1mg‐DST cortisol or frailty in the MACS and NFA groups. Conclusion Patients with CS, and those with MACS and post‐1mg‐DST cortisol > 83 nmol/L, exhibited a higher burden of osteoporosis. However, only CS was associated with an elevated risk of symptomatic fragility fractures.

BACKGROUND: Distinguishing between unilateral and bilateral primary aldosteronism, a major cause of secondary hypertension, is crucial due to different treatment approaches. While adrenal venous sampling is the gold standard, its invasiveness, limited availability, and often difficult interpretation pose challenges. This study explores the utility of circulating microRNAs (miRNAs) and machine learning in distinguishing between unilateral and bilateral forms of primary aldosteronism. 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.