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

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

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Title: Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders
Author: Kong, Sek Won; Collins, Christin D.; Shimizu-Motohashi, Yuko; Holm, Ingrid A.; Campbell, Malcolm G.; Lee, In-Hee; Brewster, Stephanie J.; Hanson, Ellen M.; Harris, Heather; Lowe, Kathryn R.; Saada, Adrianna; Mora, Andrea; Madison, Kimberly; Hundley, Rachel; Egan, Jessica; McCarthy, Jillian; Eran, Ally; Galdzicki, Michal; Rappaport, Leonard; Kunkel, Louis M.; Kohane, Isaac S.

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Citation: Kong, Sek Won, Christin D. Collins, Yuko Shimizu-Motohashi, Ingrid A. Holm, Malcolm G. Campbell, In-Hee Lee, Stephanie J. Brewster, et al. 2012. Characteristics and predictive value of blood transcriptome signature in males with autism spectrum disorders. PLoS ONE 7(12): e49475.
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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.
Published Version: doi:10.1371/journal.pone.0049475
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3515554/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10582123
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