Currently autism is diagnosed using behavioral criteria. This limits the age at which reliable diagnoses can be made. Yet, case histories tell us that early intervention leads to improved life-long outcomes. To begin intervention at the earliest possible time, priority must be given to developing unbiased approaches to predict the presence of autism. Biological markers can also help define autism subtypes and reveal potential therapeutic targets.

In biology and medicine, a biomarker is a distinctive biological or biologically derived substance that can be used to indicate the presence or progress of a condition, or to measure the effects of treatment. Diagnostic biomarkers for autism can be developed from a variety of methods. Some of the most commonly used include metabolic, genomic, or proteomic (protein) profiling. Through its Biomarker Initiative, Cure Autism Now is currently investing in metabolic profiling using lipid and urine analyses, as well as investigating early physiologic markers such as motor function.

Metabolic Profiling

In 2005 CAN/AGRE partnered with Lipomics Technologies, Inc., a biotech company specializing in lipid analysis. The study will compare the levels of many different lipids, including docosahexaenoic acid (DHA), an omega-3 essential fatty acid, in blood samples of children with Autism Spectrum Disorders with their unaffected siblings. Lipomics has begun analyzing blood samples collected by AGRE to generate lipomic profiles. AGRE and Lipomics are also collaborating with the Southwest Autism Research and Resource Center (SARRC) to recruit a normal control sample. Preliminary data analyses on the children with ASD have revealed interesting trends and AGRE will continue to work with Lipomics and other lipid researchers.

In early 2006, CAN awarded a Biomarker Initiative Bridge Grant to Manya T. Angley, Ph.D. of the University of South Australia for her project entitled "Investigation of Etiology, Determination of Prognosis and Optimization of Interventions in Autism using Metabonomics." In this project, metabonomics (which is a cutting edge technology that examines patterns of metabolites in bio-fluids) will be used to identify features in urine that are distinctive for individuals with autism. If identified, these characteristic urine profiles may potentially be used as biomarkers to confirm an autism diagnosis and to subtype different groups of children with autism, thereby offering indications for treatment opportunities.

Early Physiologic Markers

An independent method for developing early diagnostics is to test for physiologic measures apparent in young children at risk for developing autism. Recent attention has focused on motor system functioning in autistic infants and children. Studies published in the Proceedings of the National Academy of Science (Teitelbaum et al. 2004, Teitelbaum et al. 1998) suggest that lack of certain motor reflexes may be one early sign of the autism spectrum. An extraordinarily simple tilt test, designed to test the reflex that young babies have to keep their head vertical, was postulated to be diagnostic for infants at-risk for developmental disorders. Given the nature of the test (quick, easy, a very early indicator, and at no extra cost to the doctors or parents), CAN is pursuing whether motor tone and the tilt test, either alone or in combination with other metrics such as changes in head circumference, may be an early "biomarker" for a subgroup of infants at risk for developing autism. This is currently being piloted by testing on baby siblings of patients with ASD at the Neurodevelopmental Diagnostic Center for Young Children at George Washington University.

References:
Teitelbaum O, Benton T, Shah PK, Prince A, Kelly JL, Teitelbaum P.
Eshkol-Wachman movement notation in diagnosis: the early detection of Asperger's syndrome.
Proc Natl Acad Sci U S A. 2004 Aug 10;101(32):11909-14. Epub 2004 Jul 28.
PMID: 15282371

Teitelbaum P, Teitelbaum O, Nye J, Fryman J, Maurer RG.
Movement analysis in infancy may be useful for early diagnosis of autism.
Proc Natl Acad Sci U S A. 1998 Nov 10;95(23):13982-7.