Functional genomics and psychiatric illness

Abstract

The efforts to complete sequencing of the human genome have enabled new endeavors into the function of these genes in human disorders and have provided a wealth of knowledge about the molecular underpinnings of behavior. However, sequencing and mapping represent the initial step in our understanding of gene function and how gene expression is related to our health. The next major challenge in biology is the utilization of this information to determine the function of the genes and proteins in the context of human disease. The advent of high-throughput screening technologies has produced a paradigm shift in the manner in which scientists are able to detect and identify molecular mechanisms related to disease. Procedures such as serial analysis of gene expression (Velculescu et al., 1995), differential display (Liang and Pardee, 1992) and cDNA sequencing (Okubo et al., 1992) enable the assessment of differential gene expression but have limited throughput when compared to microarrays. Microarray analysis offers an alternative strategy that allows the simultaneous assessment of thousands of genes of known function as well as expressed sequence tags (ESTs) with either one or multiple samples (Brown and Botstein, 1999; Schena et al., 1995). The two most widely used types of arrays for gene expression analysis are the cDNA and oligo arrays, such as those produced by Affymetrix. Oligonucleotide arrays consist of multiple, yet distinct, representations (e.g 10-25 mers) of individual genes. The principle advantages of the technology are the specificity of hybridization of the oligonucleotides with target cDNA (enabling discrimination among gene family members as well as splice variants), the ability to perform both gene expression and single nucleotide polymorphism analysis using the same platform, good sensitivity in detection, and the ability to compare multiple array experiments post hoc. Alternatively, cDNA arrays consist of longer clone fragments (e.g. 300-2000 bases) with one to three representations of each gene on the array. (Schena et al., 1995; Derisi et al., 1996). The distinct advantages of this type of array are greater flexibility and lower relative cost and the availability of array spotters, scanners, and cDNA clones enables researchers to manufacture arrays to their respective specifications. Similar to oligo arrays, cDNA arrays can be used to make post hoc comparisons from multiple array experiments as well as to compare multiple samples on the same array. To evaluate differential gene expression, complementary DNA (cDNA) or oligonucleotides are adhered to a solid support (ie. glass, nylon, plastic). During reverse transcription, cDNA is labeled with either radioactive (e.g. 32P/ 33P dCTP or dATP) or fluorescent tagged nucleotides (eg. Cyanine 3 and 5: Cy3 and Cy5) for individual or competitive hybridization strategies, respectively. The immobilized cDNA or oligos will hybridize with the complementary labeled cDNA, such that the intensity of the hybridization signal for a specific array spot will be representative of the abundance of that particular transcript in the tissue or cell from which the RNA was extracted originally. DNA microarray technology provides a systematic parallel approach for investigating the simultaneous expression of thousands of genes - thereby enabling a global view of the multigenic nature of mental illnesses. To date, microarray analysis has been used to investigate differential gene expression in several areas of brain research including aging (Ly et al., 2000; Lee et al., 2000; Weindruch et al., 2002), multiple sclerosis (Whitney et al., 1999, 2001) and Alzheimer’s Disease (Ginsberg et al., 1999, 2000). However, the utility of microarray analysis for the investigation of molecular correlates of psychiatric illness is only now being realized. Broad scale evaluations of gene expression using microarrays are well suited to the study of psychiatric illnesses, particularly in light of the complexity of the brain compared with other tissues, the multigenic nature of these illnesses, the large representation of expressed genes in the brain, and our relatively limited knowledge of the molecular pathology of these illnesses. Examples of microarray based gene expression analysis in schizophrenia and drug abuse in both human postmortem brain tissue and animal models are presented to illustrate the achievements and limitations encountered with microarray technology in studying psychiatric illnesses.