Abstract
In order to provide an alternative approach for understanding the biology and genetics of autism, we performed statistical analysis of gene expression profiles of lymphoblastoid cell lines derived from children with autism and their families. The goal was to assess the feasibility of using this model in identifying autism-associated genes. Replicate microarray experiments demonstrated that expression data from the cell lines were consistent and highly reproducible. Further analyses identified differentially expressed genes between cell lines derived from children with autism and those derived from their normally developing siblings. These genes were then used to identify biochemical pathways potentially involved in autism. This study suggests that lymphoblastoid cell lines may be a viable tool for identifying genes associated with autism.
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Acknowledgments
This work was supported by the MIND Institute Biomarkers Initiative, MIND Institute Genomics Core, and grant number PO1 ES 11269 from the NIEHS and US EPA. The authors would like to thank AGRE for providing cells lines and information on families used in this study. The authors express their appreciation to Zeljka Smit-McBride for culturing the AGRE cell lines, to Dawn Milliken for performing the gene expression microarray work, and to Clifford Tepper and Wenting Zhang for helpful commentary during manuscript preparation. We gratefully acknowledge the resources provided by the Autism Genetic Resource Exchange (AGRE) Consortium and the participating AGRE families. The Autism Genetic Resource Exchange is a program of Cure Autism Now and is supported, in part, by grant MH64547 from the National Institute of Mental Health to Daniel H. Geschwind (PI).
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The authors Colin A. Baron, Stephenie Y. Liu contributed equally to this work.
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Baron, C.A., Liu, S.Y., Hicks, C. et al. Utilization of Lymphoblastoid Cell Lines as a System for the Molecular Modeling of Autism. J Autism Dev Disord 36, 973–982 (2006). https://doi.org/10.1007/s10803-006-0134-x
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DOI: https://doi.org/10.1007/s10803-006-0134-x