Research Interests

Genomic and bioinformatic mining for molecular clues to autism in peripheral cells

We have used large-scale gene expression profiling of lymphoblastoid lines from autistic individuals and controls to probe for biomarkers and pathways relevant to autism. Results from both monozygotic twin studies as well as from autistic-unaffected sib-pair analyses have identified genes in both signaling as well as metabolic pathways that may be related to the disorder. Bioinformatic analyses of these genes and pathways highlight canonical pathways involved in development, axon guidance, and regulation of actin networks, in addition to pathways involved in Type II diabetes and insulin signaling which may be relevant to associated gastrointestinal or other physiological symptoms. Functional analyses of gene expression patterns further suggested that alterations in cholesterol and androgen metabolism are associated with the autistic phenotype. Collectively, these studies indicate dysregulation of pathways involved in nervous system development and function that are possibly modulated by cholesterol/lipid metabolism, especially the levels of androgenic hormones, which have been implicated as factors influencing susceptibility to autism. Recently, we have analyzed over 100 lymphoblastoid cell lines derived from autistic individuals and age-matched, nonautistic controls. Using novel clustering methods based on ADIR score sheets to group the samples into several autistic phenotypes for DNA microarray analyses, we recently have obtained gene expression profiles that not only discriminate between autistic and unaffected individuals but also correlate with phenotypic variants of ASD. These distinguishing genes can potentially be used to develop a diagnostic gene panel that would be able to screen for autism as well as reveal the variant of autism that is present.

Selected Publications (Three most recent):

1. Hu, V.W., Heikka, D.S., Dieffenbach, P.B., and Ha, L. (2001) Metabolic radiolabeling: experimental tool or Trojan horse? 35S-methionine induces DNA fragmentation and p53-dependent ROS production. FASEB J. 15:1562-1568
2. Hu, V.W. and Heikka, D.S. (2000) Radiolabeling revisited: metabolic labeling with 35S-methionine inhibits cell cycle progression, proliferation, and survival. FASEB J. 14:448-454.
3. Xie, H.-q., Laird, D.W., Chang, T.-H., and Hu, V.W. (1997) A mitosis-specific phosphorylation of the gap junction protein connexin43 in human vascular cells: biochemical characterization and localization. J. Cell Biol. 137:203-210.