The "chip" as a specific genetic tool

Heterogeneous data fusion for brain tumor classification

Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this report, we present a novel machine learning framework for brain tumor classification based on heterogeneous data fusion of metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) magnetic resonance spectroscopy and gene transcriptome profiling, obtained from intact brain tumor biopsies. Our experimental results show that our novel framework outperforms any analysis using individual dataset.

Optimizing high dimensional gene expression studies for immune response following smallpox vaccination using Taqman® low density immune arrays

INTRODUCTION

We sought to determine the time and vaccinia virus dose combination that would maximize the number of acute immune response changes in response to vaccinia stimulation in preparation for a large gene expression microarray experiment.

METHODS

PBMCs from ten subjects were exposed to five vaccinia virus doses for three lengths of time. Gene expression was measured for 90 immune response genes via Taqman® Low Density Immune Arrays. Expression data were normalized via model-based non-linear normalization. Linear mixed effects model results were used to standardize changes across genes and determine the time/multiplicity of infection (MOI) combination with the largest number of changes.

RESULTS

The greatest number of changes occurred with a MOI of 5.0 and exposure time of 48 h. Further inspection revealed that most changes had occurred earlier and faded at this combination. The second highest number of changes was found at a MOI of 0.5 PFU/cell and time of 18 h.

CONCLUSIONS

We conclude a time of 18 h with a MOI of 0.5 PFU/cell is the optimal time/MOI combination for the full scale gene expression study. The strategy described herein is a general and resource efficient way to make critical decisions regarding experimental parameters for studies utilizing expensive assays that interrogate a large number of variables.

Pharmacogenomics

So far no pharmacogenetic/genomic study has been conducted specifically for anxiety disorders. Some of the presented results, however, do pertain to such disorders. For example, pharmacokinetic aspects of antidepressant drug therapy likely also apply to patients with anxiety disorders, and several genetic polymorphisms in the cytochrome P450 (CYP) gene family and drug transporter molecules, such as the multidrug resistance (MDR) gene type 1, have been reported to influence the pharmacokinetics of antidepressant drugs. At this stage of pharmacogenomics research, it is difficult to interpret the relevance of pharmacodynamic-genetic association studies conducted in depressed patients for anxiety disorders. A number of studies have reported an influence of polymorphisms of genes mostly in the serotonergic pathway on the response to antidepressant drugs in patients suffering from depression. In order to know whether they can be extrapolated to patients with anxiety disorders, clinical studies are warranted. Despite all the shortcomings of the currently available pharmacogenetic studies, this field holds great promise for the treatment of anxiety disorders. In the future, psychiatrists may be able to base treatment decisions (i.e., the type and dose of prescribed drug) on more objective parameters than only the diagnostic algorithms used now. This will limit unwanted side effects and adverse drug reactions, and could reduce time to response, resulting in a more individualized pharmacotherapy.

mRNA up-regulation of MHC II and pivotal pro-inflammatory genes in normal brain aging

In normal brain aging, CNS resident macrophages exhibit increased expression of major histocompatibility complex (MHC) II expression. However, the transcriptional basis for this observation has not been clarified nor have age-related alterations in pivotal pro-inflammatory genes been characterized. Age-related mRNA alterations in MHC II, MHC II accessory molecules and several pro-inflammatory mediators were measured in older (24 months) and younger (3 months) male F344xBN F1 rats. Real time RT-PCR was utilized to measure steady state mRNA levels in hippocampus. Older as compared to younger animals exhibited increased mRNA levels of MHC II, CD86, CIITA and IFN-gamma. Furthermore, IL-10 and CD200 mRNA, molecules that down-regulate macrophage activation, was decreased in older animals. The present results indicate that normal brain aging is characterized by a shift towards a pro-inflammatory microenvironment in the CNS.

A guide to the genetics of psychiatric disease

The road to scientific discovery begins with an awareness of what is unknown. Research in science can in some ways be like putting together the pieces of a puzzle without having the benefit of the box-top picture of the completed puzzle. The "picture" in science is an understanding of how nature works in a particular instance, and it takes many separate pieces of the "puzzle" to put this understanding together. These pieces are always of different kinds of data, often obtained using different approaches and techniques. The challenge of the researcher is to picture or hypothesize each of the missing pieces before actually having them in hand, so they can be sought and tested in the laboratory. This "picturing" is actually having a clear idea of what you don't know: having a clear image of the "shape" of the missing piece. This is easy when the puzzle surrounding the missing piece is already in hand, but more difficult with less of it constrained by what is already known. In putting paper puzzles together, the shape of the pieces is not the only limitation that needs to be satisfied. There is also the picture to satisfy, that is, the picture usually has to make sense. In science these constraints can be manifold, and usually the quality of the research is judged by the number of ways a piece of data integrates into and brings together the rest of the puzzle. The multidimensionality of scientific questions makes it virtually essential that as many different pieces of the puzzle as possible be obtained. The more that is not known about the puzzle, the more pieces you need. Thus it is with the genetics of psychiatric diseases. In this guide, we will explore as many of the domains of the genetic puzzle as we are aware of. We will learn a bit of the language of each and how they fit into the puzzle with at least one anecdote to serve as an example. Mapping unknown territory is always a process, but we hope this guide will increase the reader's awareness of what is unknown.

Initial conditions of psychotropic drug response: studies of serotonin transporter long promoter region (5-HTTLPR), serotonin transporter efficiency, cytokine and kinase gene expression relevant to depression and antidepressant outcome

The Hypothesis of Initial Conditions posits that differences in psychotropic drug response result from individual differences in receptor site kinetics, and differences in the sensitivity of downstream receptor-linked responses. This work examines data consistent with the hypothesis, specific to genetic and kinetic differences of the serotonin (5-HT) transporter (SERT), as they may be linked to divergent antidepressant response (ADR). The mechanisms for divergent ADR in association with different initial SERT function are considered within the context of SERT trafficking as sensitive to various different kinase and cytokine signals, some of which are dependent on the 5-HTTLPR polymorphism of the SERT gene. Pilot data suggest that human lymphocytes show kinase changes similar to those found in rat brain with ADT. These studies additionally suggest that ADT prompts a shift in cytokine gene expression toward a greater anti-inflammatory/inflammatory ratio. These latter findings are discussed within the context of a literature suggesting increased inflammatory cytokine levels in depression, and recent observations of increased temperature associated with depression. In sum, the data suggest the opportunity to identify response dependent protein (RDP) expression patterns that may differ with dichotomous ADR, and suggest new insights into understanding the mechanisms of psychotropic drug response through an understanding of initial differences in potential for psychotropic drug target regulation during therapy.

Quantitative comparison of cDNA-AFLP, microarrays, and GeneChip expression data in Saccharomyces cerevisiae

cDNA-AFLP is a genome-wide expression analysis technology that does not require any prior knowledge of gene sequences. This PCR-based technique combines a high sensitivity with a high specificity, allowing detection of rarely expressed genes and distinguishing between homologous genes. In this report, we validated quantitative expression data of 110 cDNA-AFLP fragments in yeast with DNA microarrays and GeneChip data. The best correlation was found between cDNA-AFLP and GeneChip data. The cDNA-AFLP data revealed a low number of inconsistent profiles that could be explained by gel artifact, overexposure, or mismatch amplification. In addition, 18 cDNA-AFLP fragments displayed homology to genomic yeast DNA, but could not be linked unambiguously to any known ORF. These fragments were most probably derived from 5' or 3' noncoding sequences or might represent previously unidentified ORFs. Genes liable to cross hybridization showed identical results in cDNA-AFLP and GeneChip analysis. Three genes, which were readily detected with cDNA-AFLP, showed no significant expression in GeneChip experiments. We show that cDNA-AFLP is a very good alternative to microarrays and since no preexisting biological or sequence information is required, it is applicable to any species.

Electric chips for rapid detection and quantification of nucleic acids

A silicon chip-based electric detector coupled to bead-based sandwich hybridization (BBSH) is presented as an approach to perform rapid analysis of specific nucleic acids. A microfluidic platform incorporating paramagnetic beads with immobilized capture probes is used for the bio-recognition steps. The protocol involves simultaneous sandwich hybridization of a single-stranded nucleic acid target with the capture probe on the beads and with a detection probe in the reaction solution, followed by enzyme labeling of the detection probe, enzymatic reaction, and finally, potentiometric measurement of the enzyme product at the chip surface. Anti-DIG-alkaline phosphatase conjugate was used for the enzyme labeling of the DIG-labeled detection probe. p-Aminophenol phosphate (pAPP) was used as a substrate. The enzyme reaction product, p-aminophenol (pAP), is oxidized at the anode of the chip to quinoneimine that is reduced back to pAP at the cathode. The cycling oxidation and reduction of these compounds result in a current producing a characteristic signal that can be related to the concentration of the analyte. The performance of the different steps in the assay was characterized using in vitro synthesized RNA oligonucleotides and then the instrument was used for analysis of 16S rRNA in Escherichia coli extract. The assay time depends on the sensitivity required. Artificial RNA target and 16S rRNA, in amounts ranging from 10(11) to 10(10) molecules, were assayed within 25 min and 4 h, respectively.

Differential HLA gene expression in measles vaccine seropositive and seronegative subjects: a pilot study

This is the first study using GeneChip technology to elucidate genetic determinants of the measles vaccine response. A comparative gene expression study was conducted using Affymetrix's Human GeneChip U-95A in 5 human subjects immunized with a 'booster' dose of measles vaccine (Attenuax, Merck) to determine whether serologically distinct subjects exhibit differential expression of human leukocyte antigen (HLA) genes. Healthy individuals aged 15-25 y, previously immunized with 2 doses of measles-mumps-rubella-II (MMR-II) vaccine, were classified as measles vaccine immunoglobulin G-specific antibody seronegatives (n = 2) and seropositives (n = 3). Changes in expression of HLA genes in seronegatives and seropositives were studied on days 7 and 14 post-measles vaccination using Microarray Suite 5.0 (MAS 5.0). There was increased expression of the HLA class I-B (p = 0.0002), HLA class II cluster of DMA, DMB, TAP1, TAP2 (p = 0.0007) and HLA-DR (p = 0.0001) genes, and decreased expression of HLA class I MICB molecule (p = 1), HLA class I-A (p = 0.9999) and major histocompatibility complex class III HSP 70 (p = 0.9999) genes on day 7 or day 14 postvaccination in seropositives compared with seronegatives. These results suggest an association between antibody response and differential HLA gene activation and may explain one potential mechanism underlying measles vaccine non-response.

Gene microarrays in hippocampal aging: statistical profiling identifies novel processes correlated with cognitive impairment

Gene expression microarrays provide a powerful new tool for studying complex processes such as brain aging. However, inferences from microarray data are often hindered by multiple comparisons, small sample sizes, and uncertain relationships to functional endpoints. Here we sought gene expression correlates of aging-dependent cognitive decline, using statistical profiling of gene microarrays in well powered groups of young, mid-aged, and aged rats (n = 10 per group). Animals were trained on two memory tasks, and the hippocampal CA1 region of each was analyzed on an individual microarray (one chip per animal). Aging- and cognition-related genes were identified by testing each gene by ANOVA (for aging effects) and then by Pearson's test (correlating expression with memory). Genes identified by this algorithm were associated with several phenomena known to be aging-dependent, including inflammation, oxidative stress, altered protein processing, and decreased mitochondrial function, but also with multiple processes not previously linked to functional brain aging. These novel processes included downregulated early response signaling, biosynthesis and activity-regulated synaptogenesis, and upregulated myelin turnover, cholesterol synthesis, lipid and monoamine metabolism, iron utilization, structural reorganization, and intracellular Ca2+ release pathways. Multiple transcriptional regulators and cytokines also were identified. Although most gene expression changes began by mid-life, cognition was not clearly impaired until late life. Collectively, these results suggest a new integrative model of brain aging in which genomic alterations in early adulthood initiate interacting cascades of decreased signaling and synaptic plasticity in neurons, extracellular changes, and increased myelin turnover-fueled inflammation in glia that cumulatively induce aging-related cognitive impairment.

Analysis of altered genomic expression profiles in the senescent and diseased myocardium using cDNA microarrays

Cardiac function deteriorates with aging or disease. Short term, any changes in heart function may be beneficial, but long term the alterations are often detrimental. At a molecular level, functional adaptations involve quantitative and qualitative changes in gene expression. Analysis of all the RNA transcripts present in a cell's population (transcriptome) offers unprecedented opportunities to map these transitions. Microarrays (chips), capable of evaluating thousands of transcripts in one assay, are ideal for transcriptome analyses. Gene expression profiling provides information about the dynamics of total genome expression in response to environmental changes and may point to candidate genes responsible for the cascade of events that result in disease or are a consequence of aging. The aim of this review is to describe how comparisons of cellular transcriptomes by cDNA array based techniques provide information about the dynamics of total gene expression, and how the results can be applied to the study of cardiovascular disease and aging.

DNA microarray technology: devices, systems, and applications

In this review, recent advances in DNA microarray technology and their applications are examined. The many varieties of DNA microarray or DNA chip devices and systems are described along with their methods for fabrication and their use. This includes both high-density microarrays for high-throughput screening applications and lower-density microarrays for various diagnostic applications. The methods for microarray fabrication that are reviewed include various inkjet and microjet deposition or spotting technologies and processes, in situ or on-chip photolithographic oligonucleotide synthesis processes, and electronic DNA probe addressing processes. The DNA microarray hybridization applications reviewed include the important areas of gene expression analysis and genotyping for point mutations, single nucleotide polymorphisms (SNPs), and short tandem repeats (STRs). In addition to the many molecular biological and genomic research uses, this review covers applications of microarray devices and systems for pharmacogenomic research and drug discovery, infectious and genetic disease and cancer diagnostics, and forensic and genetic identification purposes. Additionally, microarray technology being developed and applied to new areas of proteomic and cellular analysis are reviewed.

Microarray comparison of normal and W/Wv mice in the gastric fundus indicates a supersensitive phenotype

Interstitial cells of Cajal (ICC) have been identified in specific areas throughout the smooth musculature of the gastrointestinal (GI) tract. Located within the circular and longitudinal muscle layers of the gastric fundus lies a specific type of ICC, termed "intramuscular" ICC or IC-IM. The principal function of this cell type is to act as "mediators of excitatory and inhibitory enteric neurotransmission." The functional role of these cells has been investigated using W/W(v) mutant mice that specifically lack IC-IM, resulting in disrupted enteric neurotransmission. The aim of the present study was to investigate differential gene expression in W/W(v) mutant mice, from the tunica muscularis of the gastric fundus using a mouse cDNA microarray containing 1,081 known genes. Verification of the microarray data was attained using real-time "quantitative" PCR (qPCR). Of the 1,081 arrayed genes, 36 demonstrated differential expression by >2-fold in the W/W(v) mice. An agreement rate of 50% (7 of 14 tested) was obtained using qPCR. Of the seven confirmed changes in expression, several were indicative of a supersensitive phenotype, observed in denervation models. Expression of several putative neurotransmitter receptors including P2Y, the receptor for the inhibitory neurotransmitter ATP, was upregulated. The functional role of the P2Y receptor was also investigated using electrophysiological recordings. These results offer a new insight into the molecular changes that occur in W/W(v) fundic smooth muscle and may also provide novel information with regard to the importance of IC-IM in enteric neurotransmission.

Gene expression profiling with DNA microarrays: advancing our understanding of psychiatric disorders

DNA microarray transcriptome profiling of the postmortem brain opens novel horizons in understanding molecular changes associated with complex psychiatric disorders. With careful analysis and interpretation of microarray data we are uncovering previously unknown, expression patterns that maybe subject-specific and pivotal in understanding the disease process. In our recent studies, analyses of the prefrontal cortex of subjects with schizophrenia and matched controls uncovered complex changes in the expression of genes related to presynaptic secretory release, GABAergic and glutamatergic transmission, metabolic pathways, myelination, as well as cAMP and phosphoinositol second messenger systems. Our goal will be to integrate this expression data within the context of the relevant anatomical, biochemical, molecular, imaging and clinical findings.

New genomic avenues in behavioural neuroendocrinology

Neuroendocrine systems play a key role not only in the maintenance of whole-body homeostasis but also as the link between behavioural, endocrine and autonomic responses to environmental stimuli. It is becoming increasingly clear that neuroendocrine regulatory mechanisms are under the control of a combination of factors including genetic background, environment and early-life programming. Patterns of gene expression are increasingly being used to provide information on the genotypes associated with particular behaviours, and modulation of specific parts of the genome allow investigation of the contribution of particular genes. The sequencing of the genome provides a unique opportunity to elucidate the genetic contribution to neuroendocrine and behavioural processes, and to investigate the interactions between genetic and environmental factors. Although drugs can be used to activate or inhibit neurotransmitters and receptors, they lack specificity. New technologies now permit the activation or inactivation of both neurotransmitters and receptors in specific areas of the brain for defined periods, including crucially important developmental windows when activation appears to have long-term consequences. The future challenges are to define the critical mechanisms through which the genetic constitution of an individual human or experimental animal interacts with environmental cues to result in altered physiological or even pathological behaviour and endocrine function.

Nuclei and subnuclei gene expression profiling in mammalian brain

Information on the neuroanatomical expression of a given gene is critical to understanding its function in the central nervous system. The integration of laser capture microdissection (LCM), T7-based RNA amplification and cDNA microarrays allows for this information to be simultaneously generated for thousands of genes. To validate this integrative approach, we catalogued the gene expression profiles of seven rat brain nuclei or subnuclei. A hundred cells from the following seven brain nuclei were analyzed: locus coeruleus (LC), dorsal raphe nucleus (DR), parvocellular division (PA) and magnocellular division (MG) of the hypothalamic paraventricular nucleus (PVN) and CA1, CA3 and dentate gyrus (DG) divisions of the hippocampal formation. Of the 2145 genes investigated, 1402 genes (65%) gave a hybridization signal statistically different from the background level that was defined by non-specific hybridizations to 15 different plant genes. Validation of our microarray data on four arbitrarily selected genes was confirmed by Real-Time PCR. Previous research showing expression patterns of 'signature' genes (n=17) for specific brain nuclei are consistent with our findings. For example, as previously shown, enriched mRNA expression encoding the serotonin transporter or tyrosine hydroxylase was found in DR and LC cells, respectively. Interestingly, expression of the serotonin 5-HT(2B) receptor mRNA was also found in DR cells. We confirmed this new finding by in-situ hybridization. The hierarchical clustering analysis of gene expression shows that the two divisions of the PVN (PA and MG) are closely related to each other, as well as the three regions of the hippocampal formation (CA1, CA3 and DG), which also showed similar gene expression profiles. This study demonstrates the importance, feasibility and utility of cellular brain nuclei profiling.

Functional genomics in neuropsychiatric disorders and in neuropharmacology

The rapidly accumulating amount of information concerning gene and protein expression patterns produced by functional genomics, proteomics and bioinformatics is presently providing new targets for drug development. Furthermore, the analysis of gene expression in cells and tissues affected by a disease may reveal the underlying metabolic pathways and cellular processes affected. Finally, changes in gene expression may be used in either diagnostics or the monitoring of drug responses. This review focuses on advances in the use of functional genomics in neurological and neuropsychiatric diseases and neuropsychopharmacology. Although the number of published studies in this field is still limited, it already appears that this strategy may become a fruitful means in the analysis of the aetiology of neuropsychiatric disorders and the search for novel neuropharmacological drugs.

Antigen Microarrays for Serodiagnosis of Infectious Diseases

Background: Progress in robotic printing technology has allowed the development of high-density nucleic acid and protein arrays that have increased the throughput of a variety of assays. We generated protein microarrays by printing microbial antigens to simultaneously determine in human sera antibodies directed against Toxoplasma gondii, rubella virus, cytomegalovirus (CMV), and herpes simplex virus (HSV) types 1 and 2 (ToRCH antigens).

Methods: The antigens were printed on activated glass slides with high-speed robotics. The slides were incubated first with serum samples and subsequently with fluorescently labeled secondary antibodies. Human IgG and IgM bound to the printed antigens were detected by confocal scanning microscopy and quantified with internal calibration curves. Both microarrays and commercial ELISAs were utilized to detect serum antibodies against the ToRCH antigens in a panel of characterized human sera.

Results: The detection limit (mean + 2 SD) of the microarray assay was 0.5 pg of IgG or IgM bound to the slides. Within-slide, between-slide, and between-batch precision profiles showed CVs of 1.7–18% for all antigens. Overall, >80% concordance was obtained between microarray assays and ELISAs in the classification of sera; for T. gondii, CMV, and HSV1, concordance exceeded 90%.

Conclusions: The microarray is a suitable assay format for the serodiagnosis of infectious diseases and can be easily optimized for clinical use. The ToRCH assay performs equivalently to ELISA and may have potentially important advantages in throughput, convenience, and cost.

The ultimate chip shot: can microarray technology deliver for neuroscience?

The use of cDNA and oligonucleotide microarrays, or 'chips', is emerging as a powerful, new technology in the field of neuroscience for examining gene expression in a high-throughput fashion. The application of microarray technology to the study of brain and behavior has lagged behind other areas of biology such as cancer and yeast genetics due to the challenges presented by the heterogeneous and complex organization of the nervous system. This review provides a brief overview of available microarray technology as well as a description of experimental considerations in planning and implementing a neuroscience-based array study. Successful implementation of microarray technology within the field of neuroscience will provide a molecular approach to studying systems neurobiology, leading to insights into areas ranging from fundamental questions of developmental neurobiology to neurological and psychiatric disorders.

Optimisation of methods for selecting candidate genes from cDNA array screens: application to rat brain punches and pineal

DNA arrays are potentially powerful experimental tools within neuroscience but application of this technology to in vivo paradigms may, in practice, be limited by the sensitivity of transcript detection and inter-screen variation. Here we describe the use of brain punch micro-sampling, used in combination with commercially available cDNA arrays, for profiling brain gene expression in a mutant strain of rat (GAERS model of absence epilepsy). Furthermore, we describe a multi-step optimisation of analysis methods which provides for improved sensitivity and absence of bias in the selection of candidate genes which may be differentially expressed in the mutant. Our method has been validated through application to a second paradigm, rhythmic gene expression in the rat pineal gland. Our experimental design, and analysis method should therefore be generally applicable to subtle discriminations of transcript abundance within discrete brain areas.

Gene expression microarrays: a 21st century tool for directed vaccine design

DNA microarray technology is a new and powerful tool that allows the simultaneous analysis of a large number of nucleic acid hybridization experiments in a rapid and efficient fashion. The development of the DNA microarray chip has been driven by modern techniques of microelectronic fabrication, miniaturization and integration to produce what is referred to as "laboratory-on-chip" devices. The application of DNA chip technology includes the comprehensive analysis of multiple gene mutations and expressed sequences with regard to newer drug designs, host-pathogen interactions and the design of new vaccines. An advantage of microarray technology is that it can assist researchers to better define and understand the expression profile of a given genotype associated with disease, adverse effects from exposure to certain stimuli, or the ability to understand or predict immune responses to specific antigens. This paper briefly reviews DNA microarray technology and its implications with special reference to vaccine design. The technical aspects comprising array manufacturing and design, array hybridization, formatting, scanning and data handling are also briefly discussed.

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

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.

DNA microarrays in neuropsychopharmacology

Recent advances in experimental genomics, coupled with the wealth of sequence information available for a variety of organisms, have the potential to transform the way pharmacological research is performed. At present, high-density DNA microarrays allow researchers to quickly and accurately quantify gene-expression changes in a massively parallel manner. Although now well established in other biomedical fields, such as cancer and genetics research, DNA microarrays have only recently begun to make significant inroads into pharmacology. To date, the major focus in this field has been on the general application of DNA microarrays to toxicology and drug discovery and design. This review summarizes the major microarray findings of relevance to neuropsychopharmacology, as a prelude to the design and analysis of future basic and clinical microarray experiments. The ability of DNA microarrays to monitor gene expression simultaneously in a large-scale format is helping to usher in a post-genomic age, where simple constructs about the role of nature versus nurture are being replaced by a functional understanding of gene expression in living organisms.

Convergent functional genomics: application to bipolar disorder

The recent development of microarray technologies has made possible the simultaneous measurement of mRNA levels for thousands of genes and a new genomic method termed gene expression profiling. The application of this approach to animal models or post-mortem tissue provides a powerful tool for the discovery of novel genes involved in psychiatric disorders. This approach has strengths that are complementary to those of another genomic method for gene discovery, positional cloning. Microarray technologies and their application to post-mortem tissue and animal models of bipolar disorder are reviewed. A novel approach termed convergent functional genomics, which integrates gene profiling and positional cloning in order to rapidly identify candidate disease genes, is also described.