Gene expression profiling of lymphoblasts from autistic and nonaffected sib pairs: altered pathways in neuronal development and steroid biosynthesis

Abstract

Despite the identification of numerous autism susceptibility genes, the pathobiology of autism remains unknown. The present "case-control" study takes a global approach to understanding the molecular basis of autism spectrum disorders based upon large-scale gene expression profiling. DNA microarray analyses were conducted on lymphoblastoid cell lines from over 20 sib pairs in which one sibling had a diagnosis of autism and the other was not affected in order to identify biochemical and signaling pathways which are differentially regulated in cells from autistic and nonautistic siblings. Bioinformatics and gene ontological analyses of the data implicate genes which are involved in nervous system development, inflammation, and cytoskeletal organization, in addition to genes which may be relevant to gastrointestinal or other physiological symptoms often associated with autism. Moreover, the data further suggests that these processes may be modulated by cholesterol/steroid metabolism, especially at the level of androgenic hormones. Elevation of male hormones, in turn, has been suggested as a possible factor influencing susceptibility to autism, which affects approximately 4 times as many males as females. Preliminary metabolic profiling of steroid hormones in lymphoblastoid cell lines from several pairs of siblings reveals higher levels of testosterone in the autistic sibling, which is consistent with the increased expression of two genes involved in the steroidogenesis pathway. Global gene expression profiling of cultured cells from ASD probands thus serves as a window to underlying metabolic and signaling deficits that may be relevant to the pathobiology of autism.

Figure 1. A relational gene network constructed using Pathway Studio 5 from the dataset of significant genes identified by SAM analysis with 70% data filtering (see Table 1).

Red denotes genes with increased expression in the autistic sibling while green indicates decreased expression. Note that inflammation, epilepsy, liver disease, diabetes, and schizophrenia are among the pathological processes associated with this gene network while apoptosis, differentiation, and regulation of action potential are among the cellular processes that are influenced by this set of genes.

Figure 2. Confirmation of select differentially expressed genes by qRT-PCR analyses.

Five representative samples were analyzed per group for each gene, with each sample run in triplicate. The graph shows the average log2 ratios obtained for each gene for the 5 samples analyzed by qRT-PCR, for the same 5 samples analyzed by DNA microarrays, and for all 21 samples analyzed by DNA microarrays. *p-value<0.05; **p-value<0.004; The p-values for the qRT-PCR analysis of GATA3 was 0.069, and for the microarray analysis of SRD5A1 based on only 5 samples was 0.156. However, the p-values for GATA3 and SRD5A1 based on the microarray analysis of all 21 paired samples were <0.00006 and <0.002, respectively.

Figure 3. Common regulators (identified by Pathway Studio 5) associated with the dataset of significant differentially expressed qRT-PCR confirmed genes.

Color coding of entities associated with gene network: Red – upregulated genes; pink – other genes which are part of the regulatory network constructed by the pathway analysis program; green - small molecules; orange - functional class; purple - disorders.

Figure 4. Common targets (identified by Pathway Studio 5) associated with the dataset of significant differentially expressed qRT-PCR confirmed genes.

Colored entities are defined in legend to Fig. 3. Yellow entities describe cellular processes.

Figure 5. A bionetwork that shows the relationships and interactions between SCARB1 and SRD5A1 at the gene, protein, and metabolite levels.

Briefly, SCARB1 is responsible for the uptake of cholesterol into cells while SRD5A1 converts testosterone to 5-α-dihydrotestosterone (DHT), a more potent form of the male hormone. We propose that increases in the expression of these genes may lead to an overall increase in the production of androgens. It is also of interest that bile acid synthesis is linked to this same pathway, thereby suggesting that altered expression of these genes in ASD may lead to disturbances of bile acid synthesis in some tissues as well.

Figure 6. Separation of 1351 autistic probands (each represented by a point) into phenotypic groups on the basis of principal components analysis (PCA) of 123 scored items on the Autism Diagnostic Interview-Revised (ADIR) questionnaires for each individual which was obtained from the AGRE phenotypic database.

PCA divided the autistic individuals into 2 main groups. Hierarchical clustering of the ADIR data (data not shown) revealed that individuals in the smaller group were characterized by higher severity scores on spoken language items on the ADIR. These individuals are represented by the red points in the PCA. Hierarchical clustering also suggested 3 other phenotypic groups that were characterized by lower severity scores across all items (individuals coded blue), higher frequency of savant skills (individuals coded yellow), and intermediate severity across all items (individuals coded green). To restrict sample heterogeneity, this study used LCL only from individuals with severe language impairment (coded red) as identified by these 2 cluster analyses. Detailed methods used for the identification of distinct ASD behavioral phenotypes based on cluster analyses of ADIR scores are described by Hu and Steinberg (Autism Research (2009) in press).