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Endocr Rev. 2019 Dec 1;40(6):1605-1625. doi: 10.1210/er.2018-00262.

Steroid Metabolome Analysis in Disorders of Adrenal Steroid Biosynthesis and Metabolism.

Author information

1
Department of Biochemistry, Stellenbosch University, Stellenbosch, South Africa.
2
Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom.
3
Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, United Kingdom.
4
Department of Paediatric Endocrinology and Diabetes, Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom.
5
Department of Endocrinology, Queen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.
6
NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, United Kingdom.
7
UCSF Benioff Children's Hospital Oakland Research Institute, Oakland, California.

Abstract

Steroid biosynthesis and metabolism are reflected by the serum steroid metabolome and, in even more detail, by the 24-hour urine steroid metabolome, which can provide unique insights into alterations of steroid flow and output indicative of underlying conditions. Mass spectrometry-based steroid metabolome profiling has allowed for the identification of unique multisteroid signatures associated with disorders of steroid biosynthesis and metabolism that can be used for personalized approaches to diagnosis, differential diagnosis, and prognostic prediction. Additionally, steroid metabolome analysis has been used successfully as a discovery tool, for the identification of novel steroidogenic disorders and pathways as well as revealing insights into the pathophysiology of adrenal disease. Increased availability and technological advances in mass spectrometry-based methodologies have refocused attention on steroid metabolome profiling and facilitated the development of high-throughput steroid profiling methods soon to reach clinical practice. Furthermore, steroid metabolomics, the combination of mass spectrometry-based steroid analysis with machine learning-based approaches, has facilitated the development of powerful customized diagnostic approaches. In this review, we provide a comprehensive up-to-date overview of the utility of steroid metabolome analysis for the diagnosis and management of inborn disorders of steroidogenesis and autonomous adrenal steroid excess in the context of adrenal tumors.

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