Statistical modeling in case-control real-time RT-PCR assays, for identification of differentially expressed genes in schizophrenia.

Aspects of experimental design, statistical modeling, and statistical inference in case-control real-time reverse transcription-polymerase chain reaction (RT-PCR) assays are discussed. The background is mRNA expression data from an investigation of genes previously suggested to be schizophrenia related. Real-time RT-PCR allows large samples of individuals. However, with more individuals than positions per plate, incomplete designs are required. A basic multivariate (for several genes jointly) random-effects analysis of covariance model, incorporating heterogeneity both between and within individuals, is formulated. The use of reference genes to form additional regressors is found to be highly efficient. Because regressions between and within individuals are usually different, it is important first to average over the intraindividual replicates. This has consequences for the influence of plate effects. Topics also discussed are testing for a significant mean disease effect, differential coregulation, and the difficulty of identifying genes affected in only a subgroup of cases.

Serotonin receptor 2C (HTR2C) and schizophrenia: examination of possible medication and genetic influences on expression levels.

The serotonin receptor 2C (HTR2C) gene is of interest in schizophrenia due to its involvement in regulation of dopamine activity in the prefrontal cortex. We have previously reported a decreased expression of HTR2C mRNA levels in the prefrontal cortex of schizophrenia patients. The variability in mRNA expression levels is evaluated here more closely in relation to promoter haplotypes and neuroleptic treatment received by the patients. The decrease in HTR2C mRNA was present in neuroleptic treated individuals and in patients untreated at death, indicating that the lower expression is not a short-term medication effect. Three promoter polymorphisms were used to construct haplotypes. No SNP displayed genotypic or haplotypic association with the disease. Gene expression of HTR2C was not affected by haplotype and the expression decrease in schizophrenia patients was similar in all haplotype combinations (diplotypes). We conclude that the decrease in HTR2C expression in schizophrenia may be related to the disease mechanism rather than to drug treatment. The disease related changes in HTR2C expression are not related to the promoter variants typed in our sample, but could be due to other regulatory variants or trans-acting factors.

Decrease of serotonin receptor 2C in schizophrenia brains identified by high-resolution mRNA expression analysis.

BACKGROUND: RNA expression profiling can provide hints for the selection of candidate susceptibility genes, for formulation of hypotheses about the development of a disease, and/or for selection of candidate gene targets for novel drug development. We measured messenger RNA expression levels of 16 candidate genes in brain samples from 55 schizophrenia patients and 55 controls. This is the largest sample so far used to identify genes differentially expressed in schizophrenia brains. METHODS: We used a sensitive real-time polymerase chain reaction methodology and a novel statistical approach, including the development of a linear model of analysis of covariance type. RESULTS: We found two genes differentially expressed: monoamine oxidase B was significantly increased in schizophrenia brain (p =.001), whereas one of the serotonin receptor genes, serotonin receptor 2C, was significantly decreased (p =.001). Other genes, previously proposed to be differentially expressed in schizophrenia brain, were invariant in our analysis. CONCLUSIONS: The differential expression of serotonin receptor 2C is particularly relevant for the development of new atypical antipsychotic drugs. The strategy presented here is useful to evaluate hypothesizes for the development of the disease proposed by other investigators.

Increased monoamine oxidase messenger RNA expression levels in frontal cortex of Alzheimer's disease patients.

Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia in the industrialised world. The two monoamine oxidase (MAO) enzymes, monoamine oxidase A (MAOA) and monoamine oxidase B (MAOB), are important in the metabolism of monoamine neurotransmitters. AD and ageing have been shown to increase enzyme activity for both MAOA and MAOB. An increase (rather than decrease) of enzyme activity is a rare event in a disease that results in a decrease in the number of cells in the brain. The mechanism, transcriptional or post-transcriptional, responsible for the increase in protein activity, is not known. In this study, we investigate for the first time the messenger RNA (mRNA) expression levels of both MAOA and MAOB in 246 cortical brain samples obtained at autopsy from 62 AD patients and 61 normal controls. We found a significant increase in mRNA levels for both MAOA (P=0.001) and MAOB (P=0.002) in disease brain tissue. This indicates that both MAO enzymes might be important in the progression of AD.

Analysis of gene expression in the rat hippocampus using Real Time PCR reveals high inter-individual variation in mRNA expression levels.

In mammals, gene transcription is a step subjected to tight regulation mechanisms. In fact, changes in mRNA levels in the central nervous system (CNS) can account for numerous phenotypic differences in brain function. We performed a high-resolution analysis of mRNA expression levels for 37 genes selected from a normal rat hippocampus cDNA library. mRNA amounts were quantified using a Real Time PCR SYBR Green assay. We found that, in general, individuals from an inbred rat population (n = 20) have shown 2-3 times differences in the basal level of expression of the genes analyzed. Up to several fold differences among individuals were observed for certain genes. These inter-individual differences were obtained after correction for the different amounts of mRNA in each sample. Power calculations were performed to determine the number of individuals required to detect reliable differences in expression levels between a control and an experimental group. These data indicated that, depending on the variability of the candidate gene selected, it was necessary to analyze from five to 135 individuals in each group to detect differences of 50% in the levels of mRNA expression between two groups investigated. The comparison of mRNA abundance from different genes revealed a wide range of expression levels for the 37 genes, showing a 26,000-fold difference between the highest and lowest expressed gene.