MSACL 2019 EU Abstract

Assessing the Metabolome of Preterm Newborns: Findings from a Danish Population-based Study

Madeleine Ernst (1), Anders Bjorkbom (1), Susan Svane Laursen (1), Arieh Cohen (1)
(1) Department of Congenital Disorders, Section for Clinical Mass Spectrometry, Statens Serum Institut, Copenhagen, Denmark

Warning: Undefined variable $headshot in /var/www/html/view_abstract/view_abstract_in_program.php on line 704

Madeleine Ernst (Presenter) Statens Serum Institut

Presenter Bio: I am a scientist at the Danish National Institute for Public Health, where my research focuses around developing computational approaches and data analysis pipelines for clinical metabolomics studies. In particular, we aim at developing metabolomics approaches for dried blood spots routinely sampled from newborns for the screening of inherited diseases. Our institute performs the routine screening of all newborns in Denmark, Greenland and the Faroe Islands and also hosts the Danish National Biobank, currently comprising over 9 million biological samples.

2017-2019: Postdoc in Computational Metabolomics at the Dorrestein Lab, Uni. of California, San Diego, US
2014-2017: PhD in Plant Sciences at the Uni. of Copenhagen, DK, Marie Curie ITN MedPlant
2011-2013: MSc in Plant Metabolomics at the Uni. of São Paulo, BR
2007-2010: BSc in Pharmaceutical Sciences, Uni. of Basel, CH

Relevant Financial Disclosures (within past 24 months) No relevant financial relationship(s) to disclose. Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

INTRODUCTION:

Approximately 15 million babies worldwide are born preterm every year, and 1 million thereof die due to complications. The number of preterm birth, that is a baby born alive before 37 weeks of gestational age is constantly rising, and although some causes such as infections, diabetes or high blood pressure are known, the cause of a spontaneous preterm birth remains often unknown. A better understanding of the underlying metabolomic changes in preterm neonates could aid the development of solutions to prevent it as well as foster more feasible care and treatment options.

OBJECTIVES:

The objective of this study was to assess how the neonatal metabolome varies with gestational age and to investigate whether and how the metabolomic profile of preterm newborns differs from that of healthy term infants.

METHODS:

We used liquid chromatography tandem mass spectrometry (LC-MS/MS) in combination with metabolome mining tools, such as mass spectral molecular networking (GNPS), unsupervised substructure discovery (MS2LDA) as well as in silico annotation tools to assess the metabolomic profile from dried blood spots from over 300 neonates with varying gestational ages and health statuses sampled from the Danish National Biobank resource.

RESULTS:

We assessed the blood metabolomic profile and identified metabolites significantly varying across gestational age and with known effects also in disease etiology, such as for example bile or amino acids. Furthermore, metabolome mining tools, such as mass spectral molecular networking were revealed as powerful resources to differentiate molecules and drug metabolites from molecules likely originating from contaminating sources.

CONCLUSION:

In this study we could show that there are distinct metabolic features that vary with gestational age and that mass spectral metabolomics analysis of dried blood spots is a powerful tool to assess the metabolome of preterm neonates. With over 2 million dried blood spots, the Danish National Biobank is an exceptional resource for future large-scale integrated omics studies not only in the context of preterm birth but also for the investigation of other inborn diseases.