Metabolomics : Official journal of the Metabolomic Society · 2025
A multi-stage metabolic pattern of adrenocortical adenomas offers diagnostic potential of uric acid, isocitric acid, and proline.
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Yang Qingling, Sun Qingrong, Zhang Yunuo, Gong Renjie, Wang Majie, Li Jiankang, Lai Maode, Lai Chong
Аннотация
BACKGROUND: The development of adrenocortical adenoma (ACA) affects the endocrine homeostasis of the patient and causes various pathophysiological abnormalities. At this stage, the diagnosis of the disease and the distinguishing of adenoma subtypes in patients with ACA remains an unresolved clinical issue. Our study aimed to identify biomarkers for adenoma subtypes and their altered metabolic profiles. We also explored the metabolic differences between non-functional adenomas (NFA) of different sizes.
METHODS: In this study, we employed untargeted metabolomic analysis on a discovery set of 246 subjects and a validation set of 275 subjects. Following the construction of a biomarker diagnostic model, we proceeded to validate the model through targeted metabolomic analysis in an independent cohort of 631 participants.
RESULTS: In adenoma subtypes, the disturbed pathways in aldosterone-producing adenoma (APA), cortisol-producing adenoma (Cushing's syndrome, CS) and NFA were all mainly focused on the tricarboxylic acid cycle, purine metabolism, and lipid metabolism pathways. In NFA of different sizes, the metabolic profiles did not change significantly as the tumor increased in size. Furthermore, we successfully identified uric acid, isocitric acid, and proline as diagnostic biomarkers for ACA, 4-hydroxyestrone as a reliable marker for NFA, and LysoPC(P-16:0/0:0) for distinguishing APA from CS.
CONCLUSIONS: The plasma of patients with ACA shows significant metabolic alterations, with a similar pattern of metabolic disturbances between the different adenoma subtypes. In addition, uric acid, isocitric acid and proline combinations, 4-hydroxyestrone and LysoPC (P-16:0/0:0) could serve as potential biomarkers to complement and improve the diagnosis of ACA.
METHODS: In this study, we employed untargeted metabolomic analysis on a discovery set of 246 subjects and a validation set of 275 subjects. Following the construction of a biomarker diagnostic model, we proceeded to validate the model through targeted metabolomic analysis in an independent cohort of 631 participants.
RESULTS: In adenoma subtypes, the disturbed pathways in aldosterone-producing adenoma (APA), cortisol-producing adenoma (Cushing's syndrome, CS) and NFA were all mainly focused on the tricarboxylic acid cycle, purine metabolism, and lipid metabolism pathways. In NFA of different sizes, the metabolic profiles did not change significantly as the tumor increased in size. Furthermore, we successfully identified uric acid, isocitric acid, and proline as diagnostic biomarkers for ACA, 4-hydroxyestrone as a reliable marker for NFA, and LysoPC(P-16:0/0:0) for distinguishing APA from CS.
CONCLUSIONS: The plasma of patients with ACA shows significant metabolic alterations, with a similar pattern of metabolic disturbances between the different adenoma subtypes. In addition, uric acid, isocitric acid and proline combinations, 4-hydroxyestrone and LysoPC (P-16:0/0:0) could serve as potential biomarkers to complement and improve the diagnosis of ACA.