Horm Metab Res 2018; 50(07): 551-555
DOI: 10.1055/a-0630-1397
Endocrine Care
© Georg Thieme Verlag KG Stuttgart · New York

Could Lipid Profile be Used as a Marker of Autonomous Cortisol Secretion in Patients with Adrenal Incidentalomas?

Gesthimani Mintziori
1  Department of Endocrinology, Diabetes and Metabolism, Hippokration General Hospital of Thessaloniki, Thessaloniki, Greece
,
Thomas Georgiou
1  Department of Endocrinology, Diabetes and Metabolism, Hippokration General Hospital of Thessaloniki, Thessaloniki, Greece
,
Panagiotis Anagnostis
1  Department of Endocrinology, Diabetes and Metabolism, Hippokration General Hospital of Thessaloniki, Thessaloniki, Greece
,
Fotini Adamidou
1  Department of Endocrinology, Diabetes and Metabolism, Hippokration General Hospital of Thessaloniki, Thessaloniki, Greece
,
Zoe Efstathiadou
1  Department of Endocrinology, Diabetes and Metabolism, Hippokration General Hospital of Thessaloniki, Thessaloniki, Greece
,
Athanasios Panagiotou
1  Department of Endocrinology, Diabetes and Metabolism, Hippokration General Hospital of Thessaloniki, Thessaloniki, Greece
,
Marina Kita
1  Department of Endocrinology, Diabetes and Metabolism, Hippokration General Hospital of Thessaloniki, Thessaloniki, Greece
› Author Affiliations
Further Information

Publication History

received 10 March 2018

accepted 08 May 2018

Publication Date:
10 July 2018 (online)

Abstract

Adrenal incidentalomas (AIs) have been associated with an increased risk of metabolic syndrome and dyslipidemia, though evidence regarding the latter is limited. Lipid abnormalities in patients with AIs have been associated with subclinical hypercortisolism. The current study aims to test whether lipid profile in patients with AIs predicts “autonomous cortisol secretion” (ACS). Patients with AIs found on either computerized tomography (CT) or magnetic resonance imaging (MRI), were included in a prospective cohort study. All patients were followed up for at least three years. Alterations in their hormonal and lipid profiles were recorded. Ninety-four patients (69 women) harboring 111 AIs were included. There were no differences between patients with ACS and those without, with respect to their baseline lipid profile [total cholesterol, low-density-lipoprotein cholesterol (LDL-C), triglycerides, high-density lipoprotein cholesterol (HDL-C) and non-HDL-C] and blood pressure (systolic and diastolic). Non-HDL-C concentrations decreased over time (Repeated Measures ANOVA, p=0.013), despite patients’ body mass index (BMI) remaining unchanged. Logistic regression analysis revealed that the only predictor of ACS was the size of AIs, as calculated by CT or MRI. The current study demonstrated that lipid profile at baseline or during follow-up cannot predict ACS in patients with AIs. However, larger AIs may have a greater probability of ACS.