A Metabolism-Based Test to Diagnose Autism Spectrum Disorder and its Subtypes in Early Childhood



 DESCRIPTION (provided by applicant): Autism spectrum disorder (ASD) is now diagnosed in 1 of 68 children with recent reports citing as many as 1 in 50 children in the United States. The average age of diagnosis is more than 4 years. There is a need for a reliable biomarker-based test for earlier diagnosis of ASD in young children to improve outcomes such as cognition, social function and communication. This will subsequently decrease the financial and emotional burden on families and society. In 2012, Stemina began a self-funded Phase I equivalent study of plasma samples from nearly 400 ASD, Developmental Delay (DD) and Typically Developing (TD) children. From these studies, we developed computational models based on metabolic biomarker differences in ASD and TD children that could differentiate ASD from TD patients with an accuracy of about 80%. Stemina seeks funding to enroll 1500 patients in a well-defined clinical study to develop a biomarker-based diagnostic test capable of classifying ASD relative to other developmental delays at greater than 80% accuracy. In addition, we propose to identify metabolic subtypes present within the ASD spectrum that can be used for personalized treatment. The study will include ASD, DD and TD children between 18 and 48 months of age. Inclusion of DD patients is a novel and important aspect of this proposed study from the perspective of a commercially available diagnostic test. Our ultimate goals are to: (1) enable early diagnosis and treatment; (2) elucidate metabolic differences in subtypes of ASD patients to properly match the best available treatments for each patient from an individual biochemical perspective; and (3) identify biochemical alterations in patients across the spectrum that will provide targets for novel therapies. We will employ the innovative metabolomics approaches that we developed in Phase I, including coupling orthogonal chromatographic separation methodologies with both non- targeted and targeted high resolution mass spectrometry. Our study objectives will be to confirm biomarkers that were discovered in Phase I, expand those biomarker profiles for metabolic subtypes, and optimize the ASD test accuracy by creating panels of biomarker subtypes that will better describe this heterogeneous syndrome. Based on our Phase I data, we believe this clinical study will also allow us to confirm specific metabolic biomarkers of subtypes of ASD. This innovative approach to characterizing ASD will allow physicians to suggest the most appropriate treatment based on the individual metabolism of the patient.