including autism [5]. The possible importance of zinc is also of interest given the recent report of a decreased zinc/copper ratio in children with autism spectrum disorders [52]. Multiple lines of evidence including genetic linkage [5,6], pharmacological studies [10,11,12,53], and the associations observed in the current study suggest that variations in global levels of gene expression regulation may contribute to the risk for neurodevelopmental disorders including autism. An association of variance in gene expression with paternal age in healthy controls suggests that factors influencing global levels of gene expression regulation may be transmitted across the germ line. Findings in immune cells suggest that global levels of gene expression regulation may impact systems other than the brain. Finally, pathway analysis suggests that altered regulation of transcription may underlie decreased variance and may increase risk for autism. A more thorough understanding of the mechanisms and the biological impact of the reported associations with overall variance in gene expression represent important areas for future research. Supporting Information Figure S1 Cross-validation. Figure describes the work flow used for cross-validation. Briefly, experimental groups were divided in half to create 6 subgroups that were balance for scan batch (autism1, autism2, children of older fathers1, children of older fathers2, children of younger fathers1, children of younger fathers2). a) Shows cross-validation of changes in gene expression variance. The means of autism1, autism2, older father1, and older father 2 are lower than the means of younger father 1 and 2, but only the autism subgroups are significantly different. b) Demon- strates a significant overlap between down-regulated genes in autism1 vs. young father1 and autism2 vs. young father2 (chi- squared = 866.6, p,.00001). c) Demonstrates a significant overlap in down-regulated genes in old father1 vs. young father1 and old father2 vs. young father2 (chi-squared = 10.4, p = .0013). (TIFF) Table S1 Cross-validation of pathway analysis of down- regulated genes. Pathway analysis was done on significant gene lists (p,.05, absolute fold change .1.1) from cross-validation References 1. Newschaffer CJ, Croen LA, Daniels J, Giarelli E, Grether JK, et al. (2007) The epidemiology of autism spectrum disorders. Annu Rev Public Health 28: 235–258. 2. Sykes NH, Lamb JA (2007) Autism: the quest for the genes. Expert Rev Mol Med 9: 1–15. 3. Stephan DA (2008) Unraveling autism. Am J Hum Genet 82: 7–9. 4. Wang K, Zhang H, Ma D, Bucan M, Glessner JT, et al. (2009) Common genetic variants on 5p14.1 associate with autism spectrum disorders. Nature 459: 528–533. 5. Aso T, Shilatifard A, Conaway JW, Conaway RC (1996) Transcription syndromes and the role of RNA polymerase II general transcription factors in human disease. J Clin Invest 97: 1561–1569. 6. Zoghbi HY (2005) MeCP2 dysfunction in humans and mice. J Child Neurol 20: 736–740. 7. Enstrom AM, Lit L, Onore CE, Gregg JP, Hansen RL, et al. (2009) Altered gene expression and function of peripheral blood natural killer cells in children with autism. Brain Behav Immun 23: 124–133. 8. Gregg JP, Lit L, Baron CA, Hertz-Picciotto I, Walker W, et al. (2008) Gene expression changes in children with autism. Genomics 91: 22–29. 9. Hu VW, Frank BC, Heine S, Lee NH, Quackenbush J (2006) Gene expression profiling of lymphoblastoid cell lines from monozygotic twins discordant in severity of autism reveals differential regulation of neurologically relevant genes. BMC Genomics 7: 118. 10. Ornoy A (2009) Valproic acid in pregnancy: how much are we endangering the embryo and fetus? Reprod Toxicol 28: 1–10. 11. Schneider T, Przewlocki R (2005) Behavioral alterations in rats prenatally exposed to valproic acid: animal model of autism. Neuropsychopharmacology 30: 80–89. Autism Changes Global Gene Expression Regulation datasets (autism1 vs. younger father1, autism2 vs. young father2, old father1 vs. young father1, old father2 vs. young father 2). The table illustrates that cross-validation datasets highlighted the same enrichment of biological pathways related to transcription and zinc. (PDF) Table S2 Non-overlapping down-regulated genes. Path- way analysis was done on significant gene lists (p,.05, absolute fold change .1.1) of genes that were down-regulated in autism or in children of older fathers and not overlapping with the other group. (PDF) Table S3 Up-regulated Pathways. Pathway analysis was done on significant gene lists (p,.05, absolute fold change .1.1) of genes that were up-regulated in autism or in children of older fathers. (PDF) Table S4 Pathway analysis with increased stringency for gene list selection. Pathway analysis was done on significant gene lists (p,.05, absolute fold change .1.25, and present calls .51%) of genes that were down-regulated in autism and in children of older fathers. Table shows that the same pathways were enriched as with lower stringency gene list selection. (PDF) Acknowledgments We would like to thank Dr. Larry Abbott for advice and guidance in the measurement gene expression distributions. Author Contributions Conceived and designed the experiments: MA KR DC RM TG DS. 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(2005) Reversal of maternal programming of stress responses in adult offspring through methyl supplementation: altering epigenetic marking later in life. J Neurosci 25: 11045–11054. 17. Levenson JM, Sweatt JD (2006) Epigenetic mechanisms: a common theme in vertebrate and invertebrate memory formation. Cell Mol Life Sci 63: 1009–1016. 18. Moretti P, Levenson JM, Battaglia F, Atkinson R, Teague R, et al. (2006) Learning and memory and synaptic plasticity are impaired in a mouse model of Rett syndrome. J Neurosci 26: 319–327. 19. Fischer A, Sananbenesi F, Wang X, Dobbin M, Tsai LH (2007) Recovery of learning and memory is associated with chromatin remodelling. Nature 447: 178–182. 20. Alter MD, Rubin DB, Ramsey K, Halpern R, Stephan DA, et al. (2008) Variation in the large-scale organization of gene expression levels in the hippocampus relates to stable epigenetic variability in behavior. PLoS ONE 3: e3344. PLoS ONE | www.plosone.org 9 February 2011 | Volume 6 | Issue 2 | e16715