ReviewTarget discovery in metabolic disease
Section snippets
Expression profiling
So far, expression-profiling efforts have relied to a large extent on technologies analyzing the composition of complex mRNA samples and, less frequently, protein samples. Widely used approaches for assessing the composition of mRNA pools or differences between them are differential display, subtractive cloning or, with increasing popularity, DNA microarrays carrying probe sets that cover essentially complete genomes [7]. Tissues and organs that are of particular interest in metabolic diseases
Human genome scans
Genome-wide scans for susceptibility genes are conducted with the use of genetic polymorphisms such as simple tandem repeats or single nucleotide polymorphisms, performing linkage analysis in usually related individuals with a certain disease and/or characteristic quantifiable trait associated with the disease. A large number of human genome scans have been performed and there are comprehensive reports detailing the results for susceptibility loci associated with T2D, obesity and the metabolic
Functional screens for metabolic disease targets in model organisms
Functional screens in model organisms are a powerful approach to functionally assign genes to certain biological processes and are therefore well suited to identify key components of mechanisms controlling metabolic homeostasis. The first step usually involves mutagenesis of the genome via chemical, genetic or RNAi-based technologies, which is then followed by scoring of individual mutants or mutant lines for relevant phenotypes. Screens covering large portions of the genome have been performed
Conclusion
Target discovery in the area of metabolic diseases is a field of intense investigation, and will be for years to come, because of the obvious ethical and financial challenges for human health and healthcare systems posed by metabolic diseases. Although highly interesting targets are currently pursued in drug discovery efforts, the pathophysiological basis of metabolic diseases is only poorly understood. Identification of targets associated with the early pathophysiology of metabolic diseases
Acknowledgements
I thank the scientists at DeveloGen AG for discussions and Arnd Steuernagel for critically reading the manuscript.
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