The twin goals of this study are to use large-scale genomic methods to identify biomarkers of autism spectrum disorders (ASD) in cell lines derived from autistic individuals, and to gain a better understanding of the biology of these disorders. The central hypothesis driving this analytical approach is that blood cells from individuals with ASD will reflect molecular defects or genetic control elements that are relevant to autism. This hypothesis and approach is supported by of our preliminary findings: 1) cell lines derived from the blood of three identical twin pairs that differ in severity of ASD show a different profile of expressed genes; 2) the shared highly differentially expressed genes are significantly enriched in pathways critical to the development and function of the nervous system; 3) the levels of expression of certain genes appear to be related to the severity of the disorder when compared to the levels of expression of the same genes in cell lines from respective non-affected siblings; 4) candidate genes from preliminary microarray studies have associated quantitative trait loci containing reported autism susceptibility genes or loci. Thus, this differential expression profile which is observed in easily accessible blood-derived cells may be reflective of aberrant gene expression in the autistic vs. normal brain. This study will utilize DNA microarrays to: 1) identify differentially expressed genes in lymphoblastoid cell lines from individuals with ASD in comparison to unaffected individuals; 2) determine whether subgroups of ASD segregated according to phenotypic expression of ASD using existing diagnostic instruments, such as the ADI-R, can be differentiated through gene expression profiling; 3) build a classifier for ASD based on various class prediction algorithms, including k-nearest neighbors, centroid classification, and neural networks; 4) analyze signaling or metabolic pathways affected in the experimental subgroups; 5) map and identify genetic determinants that are responsible for differentially expressed genes using existing genetic data in the Autism Genetics Resource Exchange genotype database. At present, diagnosis of ASD relies primarily upon sometimes biased behavioral observations by clinicians or therapists and parent/teacher questionnaires. Reliable biomarkers would greatly facilitate the early and definitive detection of these disorders, thereby permitting early intervention and therapy. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21MH073393-01A2
Application #
7142718
Study Section
Developmental Brain Disorders Study Section (DBD)
Program Officer
Lehner, Thomas
Project Start
2006-08-01
Project End
2008-07-31
Budget Start
2006-08-01
Budget End
2007-07-31
Support Year
1
Fiscal Year
2006
Total Cost
$206,412
Indirect Cost
Name
George Washington University
Department
Biochemistry
Type
Schools of Medicine
DUNS #
043990498
City
Washington
State
DC
Country
United States
Zip Code
20052
Hu, Valerie W (2013) From genes to environment: using integrative genomics to build a ""systems-level"" understanding of autism spectrum disorders. Child Dev 84:89-103
Hu, Valerie W (2013) The expanding genomic landscape of autism: discovering the 'forest' beyond the 'trees' Future Neurol 8:29-42
Hu, Valerie W; Lai, Yinglei (2013) Developing a Predictive Gene Classifier for Autism Spectrum Disorders Based upon Differential Gene Expression Profiles of Phenotypic Subgroups. N Am J Med Sci (Boston) 6:
Hu, Valerie W (2012) Subphenotype-dependent disease markers for diagnosis and personalized treatment of autism spectrum disorders. Dis Markers 33:277-88
Hu, Valerie W (2011) A systems approach towards an understanding, diagnosis and personalized treatment of autism spectrum disorders. Pharmacogenomics 12:1235-8
Nguyen, AnhThu; Rauch, Tibor A; Pfeifer, Gerd P et al. (2010) Global methylation profiling of lymphoblastoid cell lines reveals epigenetic contributions to autism spectrum disorders and a novel autism candidate gene, RORA, whose protein product is reduced in autistic brain. FASEB J 24:3036-51
Hu, Valerie W; Steinberg, Mara E (2009) Novel clustering of items from the Autism Diagnostic Interview-Revised to define phenotypes within autism spectrum disorders. Autism Res 2:67-77
Hu, Valerie W; Sarachana, Tewarit; Kim, Kyung Soon et al. (2009) Gene expression profiling differentiates autism case-controls and phenotypic variants of autism spectrum disorders: evidence for circadian rhythm dysfunction in severe autism. Autism Res 2:78-97
Hu, Valerie W; Nguyen, AnhThu; Kim, Kyung Soon et al. (2009) Gene expression profiling of lymphoblasts from autistic and nonaffected sib pairs: altered pathways in neuronal development and steroid biosynthesis. PLoS One 4:e5775