OR29-2 Comprehensive Steroid and Global Metabolome Analysis by Mass Spectrometry and Machine Learning to Understand Metabolic Risk in Benign Adrenal Tumours With Mild Autonomous Cortisol Secretion

Abstract

Abstract Background Benign adrenal tumours are found in 3-10% of adults and can be non-functioning (NFAT) or associated with adrenal hormone excess. Analysing 1305 prospectively recruited patients with benign adrenal tumours, we recently demonstrated that 45% of patients had mild autonomous cortisol secretion (MACS), i.e. biochemical evidence of cortisol excess without distinct signs of Cushing syndrome (CS). We found that MACS increases the prevalence and severity of type 2 diabetes and hypertension and primarily affects women (Ann Int Med. 2022 Doi: 10.7326/M21-1737). Here we analysed the cohort's steroid metabolome and non-targeted global metabolome to reveal underlying metabolic processes. Methods We analysed 24-h urine samples from 1305 patients (649 NFAT, 591 MACS, 65 CS) using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) multi-steroid profiling assay. In addition, we performed non-targeted serum metabolome analysis in a representative sub-cohort (104 NFAT, 140 MACS, 47 CS) employing two complementary LC-MS assays, HILIC and C18-lipidomics. The steroid and global metabolome data were analysed by two supervised machine learning approaches, generalized matrix learning vector quantization and ordinal regression, to identify the most relevant metabolic changes. Findings Urine steroid metabolome analysis revealed an increase in glucocorticoid excretion from NFAT over MACS to CS, whereas androgen excretion decreased. Increased glucocorticoid metabolites were also the major differentiators between MACS patients with and without type 2 diabetes and hypertension, respectively. Lipidome analysis by machine learning identified glycerophospholipids, lysoglycerophospholipids, triacylglycerides, ceramides, sphingolipids, and acylcarnitines as the most relevant metabolite classes exhibiting gradually progressive changes with increasing cortisol excess (NFATInterpretation: We show a gradual change in the lipidome towards lipotoxicity with increasing cortisol excess. MACS patients with type 2 diabetes and hypertension had higher glucocorticoid output than other MACS patients, suggestive of a causative contribution of cortisol excess to their increased cardiometabolic burden. Observed changes may hold promise for risk stratification in MACS, a highly relevant and previously largely overlooked metabolic risk condition. Presentation: Tuesday, June 14, 2022 10:00 a.m. - 10:15 a.m.