Urinary Metabolic Signature of Primary Aldosteronism: Gender and Subtype‐Specific Alterations

• Published in: Proteomics. Clinical applications 2019-07, Vol.13 (4), p.e1800049-n/a
• Main Authors: Lana, Alessandro, Alexander, Keisha, Castagna, Annalisa, D'Alessandro, Angelo, Morandini, Francesca, Pizzolo, Francesca, Zorzi, Francesco, Mulatero, Paolo, Zolla, Lello, Olivieri, Oliviero
• Format: Article
• Language: English
• Subjects: aldosterone‐producing adenoma; aldosterone‐to‐renin ratio; Amino acids; Biomarkers - urine; Design of experiments; Endocrine disorders; Energy metabolism; Essential Hypertension - urine; Experimental design; Female; Gender; Humans; Hydroxyproline; Hyperaldosteronism - urine; Hypertension; Low molecular weights; Male; Markers; Metabolism; Metabolites; Metabolomics; Middle Aged; Molecular weight; Nitrogen; Nitrogen metabolism; primary aldosteronism; Sex Characteristics; Statistical analysis; urinary metabolomics; Variance analysis
• ISSN: 1862-8346; 1862-8354
• DOI: 10.1002/prca.201800049

Purpose The current clinical investigation for primary aldosteronism (PA) diagnosis requires complex expensive tests from the initial suspicion to the final subtype classification, including invasive approaches; therefore, appropriate markers for subtype definition are greatly desirable. The present study performs a metabolomics analysis to further examine specific molecular signatures of PA urines Experimental design The study considered PA subtype and gender‐related differences using two orthogonal advanced UHPLC‐MS metabolomics approaches. Patients with essential hypertension (n = 36) and PA (n = 50) who were referred to the outpatient hypertension clinic and matched healthy subjects (n = 10) are investigated. Results Statistically significant changes (p  1.5) of metabolites involved in central carbon, energy, and nitrogen metabolism are identified, especially purine and pyrimidine nucleosides and precursors, and free amino acids. PLS‐DA interpretation provides strong evidence of a disease‐specific metabolic pattern with dAMP, diiodothyronine, and 5‐methoxytryptophan as leading factors, and a sex‐specific metabolic pattern associated with orotidine 5‐phosphate, N‐acetylalanine, hydroxyproline, and cysteine. The results are verified using an independent sample set, which confirms the identification of specific signatures. Conclusions and clinical relevance Metabolomics is used to identify low molecular weight molecular markers of PA, which paves the way for follow‐up validation studies in larger cohorts.