Trends in Neurosciences
Volume 24, Issue 8, 1 August 2001, Pages 479-486
Journal home page for Trends in Neurosciences

Review
Analysis of complex brain disorders with gene expression microarrays: schizophrenia as a disease of the synapse

https://doi.org/10.1016/S0166-2236(00)01862-2Get rights and content

Abstract

The level of cellular and molecular complexity of the nervous system creates unique problems for the neuroscientist in the design and implementation of functional genomic studies. Microarray technologies can be powerful, with limitations, when applied to the analysis of human brain disorders. Recently, using cDNA microarrays, altered gene expression patterns between subjects with schizophrenia and controls were shown. Functional data mining led to two novel discoveries: a consistent decrease in the group of transcripts encoding proteins that regulate presynaptic function; and the most changed gene, which has never been previously associated with schizophrenia, regulator of G-protein signaling 4. From these and other findings, a hypothesis has been formulated to suggest that schizophrenia is a disease of the synapse. In the context of a neurodevelopmental model, it is proposed that impaired mechanics of synaptic transmission in specific neural circuits during childhood and adolescence ultimately results in altered synapse formation or pruning, or both, which manifest in the clinical onset of the disease.

Section snippets

Microarray choices for gene expression analysis

Currently, two widely accepted microarray types are used for gene expression analysis: oligonucleotide and cDNA microarrays 2, 20, 32, 33, 34, although both have weaknesses 12, 35. The major manufacturer of oligonucleotide arrays is Affymetrix (for a technology review, see Refs 33,36), which offers dozens of distinct microarrays. There are several advantages of the Affymetrix ‘GeneChip®’ technology, including the presence of multiple oligonucleotide features on the chip that interrogate

Limitations of microarray technology vis-á-vis brain tissue

Both cDNA microarrays and oligonucleotide GeneChips® (Affymetrix) can detect as few as one in 250 000 mRNA copies. Theoretically, this sensitivity should detect even the sparsest of mRNA species in a uniform cell population 34, 39, 40. Many low-abundance transcripts in brain samples, however, are not detected by microarrays. Unfortunately, increasing the absolute amount of the hybridized target usually will not increase the sensitivity of the microarray – the relative abundance of the

Experimental design, comparison paradigms and data interpretation

The success of individual projects depends upon the strategic design of the experimental paradigm, which is in part determined by the available starting material and the choice of array platform. For example, the use of oligonucleotide GeneChips generates microarray data that can be compared post hoc with results obtained from many other arrays of the same type. Data quality is highly dependent upon array consistency. By contrast, with fluorescence-based cDNA microarrays, expression between two

Data analysis considerations

Reporting the ‘most changed genes’ reduces the microarray approach to a high throughput northern hybridization strategy, failing to take advantage of simultaneously obtained transcriptome differences between experimental and control subjects. Many complex methods for data analysis are being developed 26, 58, 59, 60, 61, 62, 63, 64, 65. In reality, however, for neuropsychiatric disorders that involve multiple circuits and symptoms, informatics methods for discovering truly complex expression

Microarray studies related to human brain disorders

With the above-discussed technical advantages and limitations of gene expression microarrays in mind, it is no surprise that the first successful application of these methods to the study of complex neurological and psychiatric disorders has been reported only recently. Whitney et al. compared gene expression in normal white matter with that found in acute lesions from one subject with multiple sclerosis (MS) 67. In acute lesions, altered expression levels of many genes were associated with

Synaptic dysfunction in schizophrenia

Polygenic, complex disorders such as schizophrenia might ultimately benefit the most from novel functional genomics strategies. Schizophrenia affects more than 1% of the population worldwide, with clinical symptoms typically showing a late adolescence or early adulthood onset. They include a constellation of delusions, hallucinations, decreased motivation and impaired executive functions 29, 30. The underlying etiology of schizophrenia involves a combination of genetic and epigenetic factors,

A synaptic-neurodevelopmental model of schizophrenia

In light of these findings, a model is proposed 27 suggesting that different sequence mutations or polymorphisms in genes related to synaptic communication, combined with other factors, might lead to the shared clinical manifestations of schizophrenia. The basic tenets of this model have four components:

  • 1.

    The etiology of schizophrenia involves a polygenic pattern of inheritance, resulting in altered function of proteins that control the ‘mechanics’ of synaptic transmission.

  • 2.

    The heterogeneity in

Future directions

Several of the genes identified as being differentially expressed in subjects with schizophrenia have been mapped to loci implicated in the pathogenesis of the disease. However, in schizophrenia, the majority of the consistent gene expression changes might be adaptive in nature. The importance of these non-inherited changes should not be overlooked – they are potentially related to the symptoms of the disease and might prove to be useful drug targets. The key to controlling the most

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