GENE EXPRESSION PROFILING OF LYMPHOBLASTOID CELL LINES DISTINGUISHES AUTISM CASE-CONTROLS AS WELL AS AUTISTIC PHENOTYPES

Background: Autism spectrum disorders (ASD) refer to a group of related neurodevelopmental disorders characterized by delayed/abnormal language development, deficits in social interaction, repetitive behaviors and restricted interests. The heterogeneity in clinical presentation of ASD, possibly due to different etiologies, complicates genetic/biological analyses of these disorders.

Objectives: We have applied novel clustering methods to ADIR scores to identify distinct phenotypic subgroups of ASD. The purpose of this study was to identify gene expression profiles in lymphoblastoid cell lines that distinguish these subgroups from control individuals as well as to identify differentially affected pathways among the autistic groups.

Methods: DNA microarray analyses were conducted on over 115 lymphoblastoid cell lines from 3 distinct phenotypic groups of autistic individuals and age-matched, nonautistic controls from the NIMH Genetics repository. Datasets from these analyses were analyzed using Ingenuity Pathway Analysis and Pathway Studio 5 software.

Results: Comparison of gene expression profiles from control samples against all autistic samples reveals a set of genes for which gene expression level is associated with phenotypic severity. A 4-class analysis further reveals genes that separate the 3 phenotypes from each other as well as from controls. Statistical analyses of each subgroup vs. the control group identify differentially expressed genes unique to each subgroup as well as genes in common across subgroups. Bioinformatics analyses of the microarray data for each phenotypic subgroup similarly identify unique and common pathways and functions that are “enriched” in the respective gene datasets.

Conclusions: Gene expression profiles of lymphoblastoid cell lines from autistic case-controls 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 can be used to screen for autism as well as reveal the variant of autism that is present.