MSACL 2019 EU Abstract

Untargeted Metabolomic Profiles of Newborns that Will or Will Not Develop Autism: A Pilot Study on Dried Blood Spots

Julie Courraud (1,2), Susan Svane Laursen (1), Arieh Cohen (1)
(1) Department of Congenital Disorders, Neonatal Screening unit, Statens Serum Institut, Copenhagen, Denmark. (2) The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark

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Julie Courraud (Presenter) Statens Serum Institut

Presenter Bio: MSc, PharmD, and PhD in Nutritional Biochemistry

I have started as a hospital resident in medical toxicology in France and then oriented my research towards nutritional biochemistry (vitamin A, lipid and carotenoids metabolism, oxidative stress).

To come closer to the clinic, I joined the Cancer Institute of Montpellier to conduct research in clinical nutrition, cancer cachexia, as well as contributing to other fields of oncology.

After 2 years studying muscle physiology and intramuscular lipids, I combined different aspects of my background and now work in clinical metabolomics at the Statens Serum Institut in Copenhagen, Denmark.
I address various questions related to human health, especially psychiatric disorders. But I also conduct diverse methodological studies to assess the opportunities and power of metabolomics in newborn dried blood spots.

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:
Today autism spectrum disorder (ASD) is diagnosed based on behavioral signs and assessment of communication skills. In this setting, early intervention is a challenge as behavioral signs can be reliably observed only during the first years of life. Whether behavioral impairments are reflected in the blood as biochemical abnormalities is unsure, but the quest for biomarkers is legitimate, as they would represent a useful tool to help in the diagnosis and treatment of ASD and in understanding its underlying molecular mechanisms.
The etiopathology of ASD is indeed still unclear. Main risk factors include genetic and non-genetic factors, especially exposure during fetal life. If the fate of the child is already largely determined at birth, biochemical abnormalities could potentially be detectable very early in life, before behavioral signs can be detected reliably.

OBJECTIVES:
To assess whether there is a marked difference in the metabolome of newborns developing ASD versus healthy controls, we compared metabolomic profiles of newborns who have or have not been diagnosed with ASD at age 7.

METHODS:
Under the iPsych consortium agreement, we randomly selected 37 pairs of matched cases and controls all born in 2005. Cases were subjects for which a diagnosis of ASD was registered in 2012. We performed an LC-MS/MS-based untargeted metabolomics analysis of biobanked dried blood spots, i.e. whole blood collected within the first few days of life for newborn screening purposes. Raw data were preprocessed using Compound Discoverer 2.1 and putatively annotated in mzCloud. followed by multivariate statistical analyses and data visualization, including heatmaps, principal component analysis, partial least-squares discriminant analysis, and paired t-tests combined to fold-change (volcano plots).

RESULTS:
More than 1000 mass spectral features were detected, of which approx. 300 could be putatively annotated based on MS2 fragmentation patterns and library search. Various chemical classes were covered and 15 compounds were identified by comparison with pure standards (amino acids and acylcarnitines). Although the untargeted analysis revealed no clear distinction between cases and controls, we were able to pinpoint mass spectral features differentially abundant in healthy children versus children diagnosed with ASD. Data processing targeting specific subclasses of metabolites will give another perspective on the potential differences between cases and controls.

CONCLUSION:
In this unique study, untargeted metabolomic analysis of the dried blood spots did not reveal significant differences between newborns that have or have not been diagnosed with ASD at age 7. Increasing statistical power, refining selection criteria (subtypes of ASD) and targeting subclasses of metabolites could offer new opportunities to help understand the course of the disease and to contribute to an improved diagnostic process.