title: Characteristics and predictive value of blood transcriptome signature in males with autism spectrum disorders.
abstract: 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.
authors.affiliation: Informatics Program at the Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Boston Children's Hospital, Boston, Massachusetts, United States of America.
authors.forename: Sek Won
authors.initials: SW
authors.lastname: Kong
authors.forename: Christin D
authors.initials: CD
authors.lastname: Collins
authors.forename: Yuko
authors.initials: Y
authors.lastname: Shimizu-Motohashi
authors.forename: Ingrid A
authors.initials: IA
authors.lastname: Holm
authors.forename: Malcolm G
authors.initials: MG
authors.lastname: Campbell
authors.forename: In-Hee
authors.initials: IH
authors.lastname: Lee
authors.forename: Stephanie J
authors.initials: SJ
authors.lastname: Brewster
authors.forename: Ellen
authors.initials: E
authors.lastname: Hanson
authors.forename: Heather K
authors.initials: HK
authors.lastname: Harris
authors.forename: Kathryn R
authors.initials: KR
authors.lastname: Lowe
authors.forename: Adrianna
authors.initials: A
authors.lastname: Saada
authors.forename: Andrea
authors.initials: A
authors.lastname: Mora
authors.forename: Kimberly
authors.initials: K
authors.lastname: Madison
authors.forename: Rachel
authors.initials: R
authors.lastname: Hundley
authors.forename: Jessica
authors.initials: J
authors.lastname: Egan
authors.forename: Jillian
authors.initials: J
authors.lastname: McCarthy
authors.forename: Ally
authors.initials: A
authors.lastname: Eran
authors.forename: Michal
authors.initials: M
authors.lastname: Galdzicki
authors.forename: Leonard
authors.initials: L
authors.lastname: Rappaport
authors.forename: Louis M
authors.initials: LM
authors.lastname: Kunkel
authors.forename: Isaac S
authors.initials: IS
authors.lastname: Kohane
mesh_terms: D002648:Child; D002659:Child Development Disorders, Pervasive / Q000097:blood / Q000235:genetics*; D015331:Cohort Studies; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D059467:Transcriptome