Journal Article

Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders

Shimizu-Motohashi, Yuko, Madison, Kimberly, Rappaport, Leonard, Mora, Andrea, Kohane, Isaac S., Lowe, Kathryn R., Kunkel, Louis M., McCarthy, Jillian, Holm, Ingrid A., Kong, Sek Won, Campbell, Malcolm G., Galdzicki, Michal, Lee, In-Hee, Brewster, Stephanie J., Hundley, Rachel, Egan, Jessica, Collins, Christin D., Hanson, Ellen, Saada, Adrianna, Harris, Heather K., Eran, Ally

2012

Overview

Autism Spectrum Disorders (ASD) is a spectrum of highly heritable neurodevelopmental disorders in which known mutations contribute to disease risk in 20% of cases. Here, we report the results of the largest blood transcriptome study to date that aims to identify differences in 170 ASD cases and 115 age/sex-matched controls and to evaluate the utility of gene expression profiling as a tool to aid in the diagnosis of ASD. The differentially expressed genes were enriched for the neurotrophin signaling, long-term potentiation/depression, and notch signaling pathways. We developed a 55-gene prediction model, using a cross-validation strategy, on a sample cohort of 66 male ASD cases and 33 age-matched male controls (P1). Subsequently, 104 ASD cases and 82 controls were recruited and used as a validation set (P2). This 55-gene expression signature achieved 68% classification accuracy with the validation cohort (area under the receiver operating characteristic curve (AUC): 0.70 [95% confidence interval [CI]: 0.62-0.77]). Not surprisingly, our prediction model that was built and trained with male samples performed well for males (AUC 0.73, 95% CI 0.65-0.82), but not for female samples (AUC 0.51, 95% CI 0.36-0.67). The 55-gene signature also performed robustly when the prediction model was trained with P2 male samples to classify P1 samples (AUC 0.69, 95% CI 0.58-0.80). Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Age / Analysis / Autism / Biology / Blood / Brain research / Child / Child Development Disorders, Pervasive - blood / Child Development Disorders, Pervasive - genetics / Children & youth / Cohort Studies / Confidence intervals / Consortia / Disorders / Feasibility studies / Food service / Gene expression / Gene Expression Profiling / Genes / Genetic aspects / Genetics / Genomes / Genomics / Health care networks / Health risks / Health sciences / Hospitals / Humans / Informatics / Long-term depression / Long-term potentiation / Male / Males / Mathematical models / Medical schools / Medicine / Models, Genetic / Mutation / Neurodevelopmental disorders / Notch protein / Oligonucleotide Array Sequence Analysis / Pediatrics / Prediction models / Psychiatry / Signaling / Transcriptome