Gene expression in superior temporal cortex of schizophrenia patients

We investigated gene expression pattern obtained from microarray data of 10 schizophrenia patients and 10 control subjects. Brain tissue samples were obtained postmortem; thus, the different ages of the patients at death also allowed a study of the dynamic behavior of the expression patterns over a time frame of many years. We used statistical tests and dimensionality reduction methods to characterize the subset of genes differentially expressed in the two groups. A set of 10 genes were significantly downregulated, and a larger set of 40 genes were upregulated in the schizophrenia patients. Interestingly, the set of upregulated genes includes a large number of genes associated with gene transcription (zinc finger proteins and histone methylation) and apoptosis. We furthermore identified genes with a significant trend correlating with age in the control (MLL3) or the schizophrenia group (SOX5, CTRL). Assessments of correlations of other genes with the disorder (RRM1) or with the duration of medication could not be resolved, because all patients were medicated. This hypothesis-free approach uncovered a series of genes differentially expressed in schizophrenia that belong to a number of distinct cell functions, such as apoptosis, transcriptional regulation, cell motility, energy metabolism and hypoxia.

Circadian rhythms investigated on the cellular and molecular levels

Investigations on circadian rhythms have markedly advanced our understanding of health and disease with the advent of high-throughput technologies like microarrays and epigenetic profiling. They elucidated the multi-level behaviour of interactive oscillations from molecules to neuronal networks and eventually to processes of learning and memory in an impressive manner. The small-world topology of synchronized firing through neuron-neuron and neuron-glia gap junctions is discussed as a mathematical approach to these intensively studied issues. It has become evident that, apart from some disorders caused by gene mutations, the majority of disorders originating from disturbances of rhythms arise from environmental influences and epigenetic changes. In this context, it was mandatory to think of and devise experiments on temporary scales, which exponentially increased the volumes of data obtained from time-series and rapidly became prohibitive of manual inspection. Therefore, more and more sophisticated mathematical algorithms have been developed to identify rhythmic expression of genes and to find coexpression by their clustering. It is expected that disturbed rhythmic behaviour in mental disorders is reflected in altered oscillatory behaviour of gene expression.