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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.

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.