OBJECTIVES: Metabolite profiles of body fluids or tissue extracts can be regarded as important indicators of physiological or pathological states. Whether hormone-specific alterations of the serum metabolome can be identified using this technique has not been tested yet. The aim of this study was to investigate metabolic responses during hormone therapy in postmenopausal women by a nontargeted metabolomics approach. METHODS:Sixty naturally postmenopausal women were randomly assigned to treatment with testosterone undecanoate 40 mg every second day; estradiol valerate 2 mg daily; or the combination of both. Serum metabolites were determined by gas chromatography-mass spectrometry (GC-MS) before and after 3 months of treatment. Metabolites affected by the treatment were identified and correlated with changes in insulin sensitivity and lipid profiles. RESULTS: Treatment-dependent and hormone-specific effects on serum metabolites were observed, ranging between 69% reduction and 184% increase, but the metabolites that best explained the differences could not be structurally identified. Effects on annotated metabolites were less associated with clinical parameters as compared to established serum markers for adverse lipid and carbohydrate metabolism, such as cholesterol and triglycerides. However, cystine, lysine and tyrosine were shown to change in correlation with insulin sensitivity and high-density lipoprotein cholesterol levels in response to testosterone, indicating that those responses were somehow related to each other. CONCLUSIONS: Oestrogen- and androgen-specific alterations in the serum metabolome could be identified using GC-MS, reflecting hormone-specific effects on whole body metabolism. New knowledge regarding steroid-mediated metabolic responses within different tissues might be obtained using a similar approach on tissue extracts.
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OBJECTIVES: Metabolite profiles of body fluids or tissue extracts can be regarded as important indicators of physiological or pathological states. Whether hormone-specific alterations of the serum metabolome can be identified using this technique has not been tested yet. The aim of this study was to investigate metabolic responses during hormone therapy in postmenopausal women by a nontargeted metabolomics approach. METHODS: Sixty naturally postmenopausal women were randomly assigned to treatment with testosterone undecanoate 40 mg every second day; estradiol valerate 2 mg daily; or the combination of both. Serum metabolites were determined by gas chromatography-mass spectrometry (GC-MS) before and after 3 months of treatment. Metabolites affected by the treatment were identified and correlated with changes in insulin sensitivity and lipid profiles. RESULTS: Treatment-dependent and hormone-specific effects on serum metabolites were observed, ranging between 69% reduction and 184% increase, but the metabolites that best explained the differences could not be structurally identified. Effects on annotated metabolites were less associated with clinical parameters as compared to established serum markers for adverse lipid and carbohydrate metabolism, such as cholesterol and triglycerides. However, cystine, lysine and tyrosine were shown to change in correlation with insulin sensitivity and high-density lipoprotein cholesterol levels in response to testosterone, indicating that those responses were somehow related to each other. CONCLUSIONS: Oestrogen- and androgen-specific alterations in the serum metabolome could be identified using GC-MS, reflecting hormone-specific effects on whole body metabolism. New knowledge regarding steroid-mediated metabolic responses within different tissues might be obtained using a similar approach on tissue extracts.
Authors: Gordon I Smith; Dominic N Reeds; Adewole L Okunade; Bruce W Patterson; Bettina Mittendorfer Journal: J Clin Endocrinol Metab Date: 2014-04-02 Impact factor: 5.958
Authors: Matthias K Auer; Alexander Cecil; Yasmin Roepke; Charlotte Bultynck; Charlotte Pas; Johannes Fuss; Cornelia Prehn; Rui Wang-Sattler; Jerzy Adamski; Günter K Stalla; Guy T'Sjoen Journal: Sci Rep Date: 2016-11-11 Impact factor: 4.379