Horm Metab Res 2019; 51(04): 256-260
DOI: 10.1055/a-0850-9691
Endocrine Care
© Georg Thieme Verlag KG Stuttgart · New York

Metabolomics and Their Ability to Distinguish Thyroid Disorders: A Retrospective Pilot Study

Tristan Struja
1  Medical University Department, Division of Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Aarau, Switzerland
,
Andreas Eckart
1  Medical University Department, Division of Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Aarau, Switzerland
,
Alexander Kutz
1  Medical University Department, Division of Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Aarau, Switzerland
,
Peter Neyer
2  Department of Laboratory Medicine, Kantonsspital Aarau, Switzerland
,
Marius Kraenzlin
3  Endonet, Basel, Switzerland
,
Beat Mueller
1  Medical University Department, Division of Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Aarau, Switzerland
4  Medical Faculty of the University of Basel, Switzerland
,
Christian Meier
3  Endonet, Basel, Switzerland
4  Medical Faculty of the University of Basel, Switzerland
,
Luca Bernasconi*
2  Department of Laboratory Medicine, Kantonsspital Aarau, Switzerland
,
Philipp Schuetz*
1  Medical University Department, Division of Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Aarau, Switzerland
4  Medical Faculty of the University of Basel, Switzerland
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Publikationsverlauf

received 21. Oktober 2018

accepted 31. Januar 2019

Publikationsdatum:
21. Februar 2019 (eFirst)

Abstract

Early diagnosis of thyroid disorders is key to further treatment. We assessed the ability of a high-throughput proton NMR metabolomic profile to distinguish disease type amongst of Graves’ disease (n=87), Hashimoto’s thyroiditis (n=17), toxic goiter (n=11), and autoimmune thyroiditis [i. e., subacute thyroiditis (n=4), postpartum thyroiditis (n=1)]. This observational study was conducted investigating patients presenting with a thyroid disorder at a Swiss hospital endocrine referral center and an associated endocrine outpatient clinic. The main outcome was diagnosis of thyroid disorder based on classical parameters. Blood draws took place as close as possible to treatment initiation. We performed one-way ANOVA and partial least squares discriminant analysis (PLS-DA) as multivariate classification and feature ranking method. One-way ANOVA analysis yielded following significantly different metabolites, triglycerides in small VLDL, triglycerides in very small VLDL, and triglycerides in large LDL (FDR=0.04). There was no distinct separation of any of the 4 diagnoses by PLS-DA. We did not find a metabolomic biomarker combination capable of predicting diagnosis. Preanalytical issues might have influenced our results. We strongly suggest replicating our work in another cohort.

* Equally contributing senior authors.


Supplementary Material