Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children.

BACKGROUND: The diagnosis of autism spectrum disorder (ASD) at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age. OBJECTIVES: To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD) children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment. METHODS: Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD. RESULTS: A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set. CONCLUSIONS: This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1) determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2) gaining new insight into the biochemical mechanisms of various subtypes of ASD 3) identifying biomolecular targets for new modes of therapy, and 4) providing the basis for individualized treatment recommendations.

Metabolic biomarkers of prenatal alcohol exposure in human embryonic stem cell-derived neural lineages.

BACKGROUND: Fetal alcohol spectrum disorders (FASD) are a leading cause of neurodevelopmental disability. The mechanisms underlying FASD are incompletely understood, and biomarkers to identify those at risk are lacking. Here, we perform metabolomic analysis of embryoid bodies and neural lineages derived from human embryonic stem (hES) cells to identify the neural secretome produced in response to ethanol (EtOH) exposure. METHODS: WA01 and WA09 hES cells were differentiated into embryoid bodies, neural progenitors, or neurons. Cells along this progression were cultured for 4 days with 0, 0.1, or 0.3% EtOH. Supernatants were subjected to C18 chromatography followed by ESI-QTOF-MS. Features were annotated using public databases, and the identities of 4 putative biomarkers were confirmed with purified standards and comparative MS/MS. RESULTS: EtOH treatment induced statistically significant changes to metabolite abundance in human embryoid bodies (180 features), neural progenitors (76 features), and neurons (42 features). There were no shared significant features between different cell types. Fifteen features showed a dose-response to EtOH. Four chemical identities were confirmed: L-thyroxine, 5'-methylthioadenosine, and the tryptophan metabolites, L-kynurenine and indoleacetaldehyde. One feature with a putative annotation of succinyladenosine was significantly increased in both EtOH treatments. Additional features were selective to EtOH treatment but were not annotated in public databases. CONCLUSIONS: EtOH exposure induces statistically significant changes to the metabolome profile of human embryoid bodies, neural progenitors, and neurons. Several of these metabolites are normally present in human serum, suggesting their usefulness as potential serum FASD biomarkers. These findings suggest the biochemical pathways that are affected by EtOH in the developing nervous system and delineate mechanisms of alcohol injury during human development.

Predicting human developmental toxicity of pharmaceuticals using human embryonic stem cells and metabolomics.

Teratogens, substances that may cause fetal abnormalities during development, are responsible for a significant number of birth defects. Animal models used to predict teratogenicity often do not faithfully correlate to human response. Here, we seek to develop a more predictive developmental toxicity model based on an in vitro method that utilizes both human embryonic stem (hES) cells and metabolomics to discover biomarkers of developmental toxicity. We developed a method where hES cells were dosed with several drugs of known teratogenicity then LC-MS analysis was performed to measure changes in abundance levels of small molecules in response to drug dosing. Statistical analysis was employed to select for specific mass features that can provide a prediction of the developmental toxicity of a substance. These molecules can serve as biomarkers of developmental toxicity, leading to better prediction of teratogenicity. In particular, our work shows a correlation between teratogenicity and changes of greater than 10% in the ratio of arginine to asymmetric dimethylarginine levels. In addition, this study resulted in the establishment of a predictive model based on the most informative mass features. This model was subsequently tested for its predictive accuracy in two blinded studies using eight drugs of known teratogenicity, where it correctly predicted the teratogenicity for seven of the eight drugs. Thus, our initial data shows that this platform is a robust alternative to animal and other in vitro models for the prediction of the developmental toxicity of chemicals that may also provide invaluable information about the underlying biochemical pathways.

Non-cell-autonomous effect of human SOD1 G37R astrocytes on motor neurons derived from human embryonic stem cells.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by motor neuron death. ALS can be induced by mutations in the superoxide dismutase 1 gene (SOD1). Evidence for the non-cell-autonomous nature of ALS emerged from the observation that wild-type glial cells extended the survival of SOD1 mutant motor neurons in chimeric mice. To uncover the contribution of astrocytes to human motor neuron degeneration, we cocultured hESC-derived motor neurons with human primary astrocytes expressing mutated SOD1. We detected a selective motor neuron toxicity that was correlated with increased inflammatory response in SOD1-mutated astrocytes. Furthermore, we present evidence that astrocytes can activate NOX2 to produce superoxide and that effect can be reversed by antioxidants. We show that NOX2 inhibitor, apocynin, can prevent the loss of motor neurons caused by SOD1-mutated astrocytes. These results provide an assay for drug screening using a human ALS in vitro astrocyte-based cell model.

Stemina biomarker discovery.

Stemina Biomarker Discovery was established in 2006 to commercialize technology developed by Dr Gabriela Cezar at the University of Wisconsin (WI, USA). Stemina's cell-based assays arise from the strategic convergence of two cutting edge technologies: metabolomics and human embryonic stem (hES) cells. Stemina analyzes the small molecules secreted by hES cells and differentiated cell types such as neural and heart cells derived from hES cells by liquid chromatography mass spectrometry at its state-of-the-art facilities in Madison, WI, USA. Stemina's first technology platform has identified a dynamic set of small molecules in the extracellular secretome of hES cells secreted in response to exposure to a library of known teratogens. Alterations to small molecules in the biochemical pathway(s) of hES cells are mapped in silico to identify biomarkers of toxicity for drug screening and development in an all human system. These small human molecules may then be translated in vivo as biomarkers of toxic response and disease.

Identification of small molecules from human embryonic stem cells using metabolomics.

Metabolomics enables the discovery of small molecules that may serve as candidate biomarkers of pharmacological efficacy or toxicity. Biochemical pathways of human development are likely active in human embryonic stem (hES) cells and derivatives, since they recapitulate organogenesis in vitro. We hypothesized that small molecules could be measured from undifferentiated hES cells and hES cell-derived neural precursors (hNPs) using metabolomics and that these compounds are altered in response to known disruptors of human development. Metabolite profiling was performed in hES cells and hNPs after exposure to valproate, an inducer of neurodevelopmental disorders. Kynurenine, an intermediate in tryptophan metabolism, and other small molecules in glutamate metabolism were significantly upregulated in response to valproate. Thus, for the first time, we have been able to measure and identify small molecules secreted from hES cells and cells derived from hES cells. The hES cell metabolome may thus serve as a source of candidate biomarkers to predict or measure pharmacological efficacy or toxic response.

Use and application of stem cells in toxicology.

In recent years, stem cells have been the subject of increasing scientific interest because of their utility in numerous biomedical applications. Stem cells are capable of renewing themselves; that is, they can be continuously cultured in an undifferentiated state, giving rise to more specialized cells of the human body such as heart, liver, bone marrow, blood vessel, pancreatic islet, and nerve cells. Therefore, stem cells are an important new tool for developing unique, in vitro model systems to test drugs and chemicals and a potential to predict or anticipate toxicity in humans. The following review provides an overview of the applications of stem cell technology in the area of toxicology. Specifically, this review addresses core technologies that are emerging in the field and how they could fulfill critical safety issues such as QT prolongation and hepatotoxicity, two leading causes of failures in preclinical development of new therapeutic drugs. We report how adult stem cells derived from various sources, such as human bone marrow and placenta, can potentially generate suitable models for cardiotoxicity, hepatotoxicity, genotoxicity/epigenetic and reproductive toxicology screens. Additionally, this review addresses the role and advantages of embryonic stem cells in the aforementioned models for toxicity and how genetic selection is employed to overcome major limitations to the implementation of stem cell-based in vitro models for toxicology.