Journal of Autism and Developmental Disorders

, Volume 36, Issue 8, pp 973–982 | Cite as

Utilization of Lymphoblastoid Cell Lines as a System for the Molecular Modeling of Autism

  • Colin A. Baron
  • Stephenie Y. Liu
  • Chindo Hicks
  • Jeffrey P. Gregg
Original Paper

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.

Keywords

Autism Lymphoblastoid cell lines Gene expression Microarray Blood genomics PathwayAssist 

References

  1. American Psychiatric Association (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC.Google Scholar
  2. Anderson, G. M., Freedman, D. X., Cohen, D. J., Volkmar, F. R., Hoder, E. L., McPhedran, P., Minderaa, R. B., Hansen, C. R., & Young, J. G. (1987). Whole blood serotonin in autistic and normal subjects. Journal of Child Psychology and Psychiatry, 28, 885–900.PubMedCrossRefGoogle Scholar
  3. Bailey, A., Le Couteur, A., Gottesman, I., Bolton, P., Simonoff, E., Yuzda, E., & Rutter, M. (1995). Autism as a strongly genetic disorder: Evidence from a British twin study. Psychological Medicine, 25, 63–77.PubMedCrossRefGoogle Scholar
  4. Bakay, M., Chen, Y. W., Borup, R., Zhao, P., Nagaraju, K., & Hoffman, E. P. (2002). Sources of variability and effect of experimental approach on expression profiling data interpretation. BMC Bioinformatics, 3, 4.PubMedCrossRefGoogle Scholar
  5. Buxbaum, J. D., Silverman, J. M., Smith, C. J., Kilifarski, M., Reichert, J., Hollander, E., Lawlor, B. A., Fitzgerald, M., Greenberg, D. A., & Davis, K. L. (2001). Evidence for a susceptibility gene for autism on chromosome 2 and for genetic heterogeneity. American Journal of Human Genetics, 68, 1514–1520.PubMedCrossRefGoogle Scholar
  6. Cheung, V. G., Conlin, L. K., Weber, T. M., Arcaro, M., Jen, K. Y., Morley, M., & Spielman, R. S. (2003). Natural variation in human gene expression assessed in lymphoblastoid cells. Nature Genetics, 33, 422–425.PubMedCrossRefGoogle Scholar
  7. Geschwind, D. H., & Gregg, J. P. (2002). Microarrays for the Neurosciences: An Essential Guide. Cambridge, MA: The MIT Press.Google Scholar
  8. Geschwind, D. H., Sowinski, J., Lord, C., Iversen, P., Shestack, J., Jones, P., Ducat, L., & Spence, S. J. (2001). The autism genetic resource exchange: a resource for the study of autism and related neuropsychiatric conditions. American Journal of Human Genetics, 69, 463–466.PubMedCrossRefGoogle Scholar
  9. Gingrich, J. A., & Hen, R. (2001). Dissecting the role of the serotonin system in neuropsychiatric disorders using knockout mice. Psychopharmacology (Berl), 155, 1–10.CrossRefGoogle Scholar
  10. Gordon, C. T., State, R. C., Nelson, J. E., Hamburger, S. D., & Rapoport, J. L. (1993). A double-blind comparison of clomipramine, desipramine, and placebo in the treatment of autistic disorder. Archives of General Psychiatry, 50, 441–447.PubMedGoogle Scholar
  11. Herrero, J., Al-Shahrour, F., Diaz-Uriarte, R., Mateos, A., Vaquerizas, J. M., Santoyo, J., & Dopazo, J. (2003). GEPAS: A web-based resource for microarray gene expression data analysis. Nucleic Acids Research, 31, 3461–3467.PubMedCrossRefGoogle Scholar
  12. Kakiuchi, C., Iwamoto, K., Ishiwata, M., Bundo, M., Kasahara, T., Kusumi, I., Tsujita, T., Okazaki, Y., Nanko, S., Kunugi, H., Sasaki, T., & Kato, T. (2003). Impaired feedback regulation of XBP1 as a genetic risk factor for bipolar disorder. Nature Genetics, 35, 171–175.PubMedCrossRefGoogle Scholar
  13. Kerr, M. K., & Churchill, G. A. (2001). Bootstrapping cluster analysis: assessing the reliability of conclusions from microarray experiments. Proceedings of the National Academy of Sciences of the United States of America, 98, 8961–8965.PubMedCrossRefGoogle Scholar
  14. Liu, J., Nyholt, D. R., Magnussen, P., Parano, E., Pavone, P., Geschwind, D., Lord, C., Iversen, P., Hoh, J., Ott, J., & Gilliam, T. C. (2001). A genomewide screen for autism susceptibility loci. American Journal of Human Genetics, 69, 327–340.PubMedCrossRefGoogle Scholar
  15. Lord, C., Pickles, A., McLennan, J., Rutter, M., Bregman, J., Folstein, S., Fombonne, E., Leboyer, M., & Minshew, N. (1997). Diagnosing autism: Analyses of data from the Autism Diagnostic Interview. Journal of Autism and Developmental Disorders, 27, 501–517.PubMedCrossRefGoogle Scholar
  16. Lord, C., Risi, S., Lambrecht, L., Cook, E., Leventhal, B., DiLavore, P., Pickles, A., & Rutter, M. (2000). The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30, 205–223.PubMedCrossRefGoogle Scholar
  17. Lord, C., Rutter, M., & Le Couteur, A. (1994). Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. Journal of Autism and Developmental Disorders, 24, 659–685.PubMedCrossRefGoogle Scholar
  18. Lu, A., Tang, Y., Ran, R., Clark, J. F., Aronow, B. J., & Sharp, F. R. (2003). Genomics of the periinfarction cortex after focal cerebral ischemia. Journal of Cerebral Blood Flow and Metabolism, 23, 786–810.PubMedGoogle Scholar
  19. Luiselli, J. K., Blew, P., Keane, J., Thibadeau, S., & Holzman, T. (2000). Pharmacotherapy for severe aggression in a child with autism: “open label” evaluation of multiple medications on response frequency and intensity of behavioral intervention. Journal of Behavior Therapy and Experimental Psychiatry, 31, 219–230.PubMedCrossRefGoogle Scholar
  20. Luo, Z., & Geschwind, D. H. (2001). Microarray applications in neuroscience. Neurobiology of Disease, 8, 183–193.PubMedCrossRefGoogle Scholar
  21. Mukherjee, S., Tamayo, P., Rogers, S., Rifkin, R., Engle, A., Campbell, C., Golub, T. R., & Mesirov, J. P. (2003). Estimating dataset size requirements for classifying DNA microarray data. Journal of Computational Biology, 10, 119–142.PubMedCrossRefGoogle Scholar
  22. Philippe, A., Guilloud-Bataille, M., Martinez, M., Gillberg, C., Rastam, M., Sponheim, E., Coleman, M., Zappella, M., Aschauer, H., Penet, C., Feingold, J., Brice, A., & Leboyer, M. (2002). Analysis of ten candidate genes in autism by association and linkage. American Journal of Medical Genetics, 114, 125–128.PubMedCrossRefGoogle Scholar
  23. Pickles, A., Bolton, P., Macdonald, H., Bailey, A., Le Couteur, A., Sim, C., & Rutter M. (1995). Latent-class analysis of recurrence risks for complex phenotypes with selection and measurement error: a twin and family history study of autism. American Journal of Human Genetics, 57, 717–726.PubMedGoogle Scholar
  24. Posey, D. I., Litwiller, M., Koburn, A., & McDougle, C. J. (1999). Paroxetine in autism. Journal of American Academy of Child and Adolescent Psychiatry, 38, 111–112.CrossRefGoogle Scholar
  25. Posey, D. J., & McDougle, C. J. (2000). The pharmacotherapy of target symptoms associated with autistic disorder and other pervasive developmental disorders. Harvard Review of Psychiatry, 8, 45–63.PubMedCrossRefGoogle Scholar
  26. Purcell, A. E., Jeon, O. H., Zimmerman, A. W., Blue, M. E., & Pevsner, J. (2001). Postmortem brain abnormalities of the glutamate neurotransmitter system in autism. Neurology, 57, 1618–1628.PubMedGoogle Scholar
  27. Rea, M. A., Gregg, J. P., Qin, Q., Phillips, M. A., & Rice, R. H. (2003). Global alteration of gene expression in human keratinocytes by inorganic arsenic. Carcinogenesis, 24, 747–756.PubMedCrossRefGoogle Scholar
  28. Risch, N., Spiker, D., Lotspeich, L., Nouri, N., Hinds, D., Hallmeyer, J., Kalaydjieva, L., McCague, P., Dimiceli, S., & Pitts, T. (1999). A genomic screen of autism: Evidence for a multilocus etiology. American Journal of Human Genetics, 65, 493–507.PubMedCrossRefGoogle Scholar
  29. Robinson, P. D., Schutz, C. K., Macciardi, F., White, B. N., & Holden, J. J. (2001). Genetically determined low maternal serum dopamine beta-hydroxylase levels and the etiology of autism spectrum disorders. American Journal of Medical Genetics, 100, 30–36.PubMedCrossRefGoogle Scholar
  30. Schadt, E. E., Monks, S. A., Drake, T. A., Lusis, A. J., Che, N., Colinayo, V., Ruff, T. G., Milligan, S. B., Lamb, J. R., Cavet, G., Linsley, P. S., Mao, M., Stoughton, R. B., & Friend, S. H. (2003). Genetics of gene expression surveyed in maize, mouse and man. Nature, 422, 297–302.PubMedCrossRefGoogle Scholar
  31. Tang, Y., Glauser, T. A., Gilbert, D. L., Hershey, A. D., Privitera, M. D., Ficker, D. M., Szaflarski, J. P., & Sharp, F. R. (2004). Valproic acid blood genomic expression patterns in children with epilepsy – a pilot study. Acta Neurologica Scandinavica, 109, 159–168.PubMedCrossRefGoogle Scholar
  32. Tang, Y., Nee, A. C., Lu, A., Ran, R., & Sharp, F. R. (2003). Blood genomic expression profile for neuronal injury. Journal of Cerebral Blood Flow and Metabolism, 23, 310–319.PubMedGoogle Scholar
  33. Unger, M. A., Rishi, M., Clemmer, V. B., Hartman, J. L., Keiper, E. A., Greshock, J. D., Chodosh, L. A., Liebman, M. N., & Weber, B. L. (2001). Characterization of adjacent breast tumors using oligonucleotide microarrays. Breast Cancer Research, 3, 336–341.PubMedCrossRefGoogle Scholar
  34. Warren, R. P., Margaretten, N. C., Pace, N. C., & Foster, A. (1986). Immune abnormalities in patients with autism. Journal of Autism and Developmental Disorders, 16, 189–197.PubMedCrossRefGoogle Scholar
  35. World Health Organization (1993). The ICD-10 classification for mental and behavioral disorders: diagnostic criteria for research ed. Geneva, Switzerland: World Health Organization.Google Scholar
  36. Yonan, A. L., Alarcon, M., Cheng, R., Magnusson, P. K., Spence, S. J., Palmer, A. A., Grunn, A., Juo, S. H., Terwilliger, J. D., Liu, J., Cantor, R. M., Geschwind, D. H., & Gilliam, T. C. (2003). A genomewide screen of 345 families for autism-susceptibility loci. American Journal of Human Genetics, 73, 886–897.PubMedCrossRefGoogle Scholar
  37. Zien, A., Aigner, T., Zimmer, R., & Lengauer, T. (2001). Centralization: a new method for the normalization of gene expression data. Bioinformatics, 17(Suppl 1), S323–S331.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Colin A. Baron
    • 1
  • Stephenie Y. Liu
    • 1
  • Chindo Hicks
    • 1
  • Jeffrey P. Gregg
    • 1
  1. 1.Department of Pathology and Laboratory Medicine and MIND InstituteUniversity of California, DavisSacramentoUSA

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