Parasiliti-Caprino, Mirko

Abstract Background Primary aldosteronism (PA) is a common treatable cause of hypertension. When caused by unilateral adrenal disease, it is potentially curable by adrenalectomy. However, specialized tests and other factors may delay definitive treatment. We assessed the time to adrenalectomy (TTA) for patients worldwide. Methods We conducted an international, multicentre retrospective study involving 39 centres from 15 countries to determine the total time taken from the first presentation to adrenalectomy and the intervals between each stage (screening, confirmatory, subtyping, and adrenalectomy). We included patients with PA who underwent adrenalectomy from January 1, 2018, to October 30, 2022. Post-adrenalectomy outcomes were evaluated using the Primary Aldosteronism Surgery Outcome criteria. We performed multivariable quantile and linear regression to identify characteristics associated with longer TTA. Results We included 861 patients, mean age 49.3 ± 11.1 years, and 44.5% were women. Overall median TTA was 13.5 months, IQR: 6.6-24.5. Median intervals were 0.1 months (screening), 1.0 months (confirmatory), 4.1 months (subtyping), and 4.3 months (adrenalectomy). On multivariable analysis, median TTA was increased by 5.4 months for each additional adrenal vein sampling (AVS) procedure. Other factors associated with longer TTA included adrenalectomy post-COVID-19, younger age, and additional screening tests. Compared with countries with routine AVS, those without AVS had a shorter TTA (6.1 vs 15.1 months, P < .001), but greater likelihood of absent/partial biochemical success post-adrenalectomy (27.4% vs 12.4%, P < .001). Conclusion Primary aldosteronism management is time-consuming worldwide, especially for subtyping tests and adrenalectomy. While omitting AVS reduces overall time, patients are less likely to achieve biochemical cure post-adrenalectomy.

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.

Abstract Disclosure: B. Vekony: None. G. Nyiro: None. Z. Herold: None. J. Fekete: None. F. Ceccato: None. S. Gruber: None. L. Kurzinger: None. M. Parasiliti-Caprino: None. B. Szeredas: None. S.K. Nazri: None. V. Fell: None. M. Bassiony: None. E.A. Azizan: None. I. Bancos: None. F. Beuschlein: None. P. Igaz: None. Background: The differentiation of uni- and bilateral forms of primary aldosteronism (PA) is of pivotal clinical relevance. Whereas unilateral PA warrants surgical treatment, bilateral PA is treated by aldosterone antagonists. The most reliable way to differentiate these two entities is adrenal venous sampling (AVS) that is an invasive method with limited availability and requiring great expertise. Aim: To develop a circulating blood-borne microRNA-based approach using machine learning for the differentiation of uni- and bilateral PA. Methods: Circulating microRNA profiling on an Illumina MiSeq platform was performed on total RNA samples isolated from EDTA-anticoagulated blood specimens taken by AVS from 18 pairs of right and left suprarenal veins (10 uni-, 8 bilateral PA). Significantly differentially expressed microRNAs were analyzed by a neural network (90-10% learner-tester cross-validation simulation). From the top 29 significantly differentially expressed microRNAs, 9 were selected for validation by Taqman RT-qPCR on a separate cohort of 30 AVS-confirmed samples (15-15 uni- and bilateral forms) both on plasma samples from adrenal as well as from peripheral veins. The method was finally tested on another independent cohort of peripheral blood samples from 80 patients (40 uni- and 40 bilateral PA). Results: Regarding the 9 microRNAs selected for validation, microRNA abundance was non-significantly lower in peripheral samples compared to AVS samples. By analyzing peripheral plasma samples, ten combinations of 4-8 microRNAs from the pool of 9 microRNAs turned out to have maximal sensitivity and specificity values over 85 %. The best combination included 6 microRNAs with a sensitivity of 86.3 % and a specificity of 87.91 % (AUC = 0.871). The inclusion of further parameters such as imaging, potassium and renin levels did not improve the model’s performance. Conclusion: The analysis of circulating blood-borne microRNAs represents a minimally invasive and potentially reliable way of differentiating uni- and bilateral PA. If bilateral PA is confirmed by the model, no more localization efforts would be necessary thus simplifying the management of PA patients. This would be relevant both from the patient’s and a public health perspective. Presentation: 6/3/2024

Background Accumulating evidence suggests that primary aldosteronism (PA) is associated with several features of the metabolic syndrome, in particular with obesity, type 2 diabetes mellitus, and dyslipidemia. Whether these manifestations are primarily linked to aldosterone-producing adenoma (APA) or bilateral idiopathic hyperaldosteronism (IHA) remains unclear. The aim of the present study was to investigate differences in metabolic parameters between APA and IHA patients and to assess the impact of treatment on these clinical characteristics. Methods We conducted a retrospective multicenter study including 3566 patients with APA or IHA of Caucasian and Asian origin. We compared the prevalence of metabolic disorders between APA and IHA patients at the time of diagnosis and 1-year post-intervention, with special references to sex differences. Furthermore, correlations between metabolic parameters and plasma aldosterone, renin, or plasma cortisol levels after 1 mg dexamethasone (DST) were performed. Results As expected, APA patients were characterized by higher plasma aldosterone and lower serum potassium levels. Only female IHA patients demonstrated significantly worse metabolic parameters than age-matched female APA patients, which were associated with lower cortisol levels upon DST. One-year post-intervention, female adrenalectomized patients showed deterioration of their lipid profile, when compared to patients treated with mineralocorticoid receptor antagonists. Plasma aldosterone levels negatively correlated with the BMI only in APA patients. Conclusions Metabolic alterations appear more prominent in women with IHA. Although IHA patients have worse metabolic profiles, a correlation with cortisol autonomy is documented only in APAs, suggesting an uncoupling of cortisol action from metabolic traits in IHA patients.