Abstract
The complex nature and polygenic determination of most bone disorders require new approaches to search for genes and genetic mechanisms underlying these diseases. The present article overviews powerful and promising methodologies, which have been used to study these disorders. One of the most commonly used approaches is that of candidate gene association study, which seeks to test the association between a particular genetic variant (i.e. allele) and a specific phenotypes. These candidate genes are identified a priori based on known biologic function of gene product. As a complement of the candidate gene approach, the whole-genome scan studies employ polymorphic makers throughout the human genome to search genomic regions responsible for determining a trait of interest by linkage and / or linkage disequilibrium analyses. High-throughput methods for differential gene expression profiling are another powerful approach for searching genes underlying complex traits. Depending on their design, these methods allow researchers to get a “snapshot” of either the whole genome or any part. Importantly, in contrast to the various linkage or linkage disequilibrium tests, gene expression profiling provides information about how genes contribute to a trait. These methods of gene expression analysis are a rapidly developing field of functional genomics. It has a very high potential for applications in bone field, including diagnostics, prevention, and treatment of complex bone disorders. Genes usually function via the protein level. Based on the two-dimensional polyacrylamide gel electrophoresis, mass spectrometry and the yeast two-hybrid techniques, proteomics becomes a potentially useful tool for identifying genes and gene functions underlying complex traits. Focused on protein expression profiles and protein-protein interactions, proteomics turns out to be a complement to functional genomics and one of the best ways to clarify complicated biochemical mechanisms underlying complex bone disorders. Promisingly, proteomics may be eventually applied to seeking and screening genes and drug targets for complex bone disorders.
Keywords: Bone Disorders, proteomics, protein-protein interactions