Choosing candidates identified by positional cloning in animal models combines the high power of candidate studies with the benefits of hypothesis-free mapping. Mapping in animal models therefore emerged as an attractive alternative. Neither of these strategies has been successful in mapping genes that control complex diseases, such as rheumatoid arthritis (RA), in humans. The most interesting prospect of gene mapping, however, is that hypothesis-free mapping can point to previously unknown and unexpected disease pathways. The major disadvantage of candidate studies is the need for a starting hypothesis to choose candidates. Until recently, candidate gene studies were the only realistic way to utilize patient materials for association studies. This increases mapping precision dramatically but it requires large repositories of patient materials and very closely spaced genetic markers, creating a need for correction for multiple testing, which raises the threshold for claiming statistical significance. Association studies compare large unrelated groups of patients with the healthy population to find regions that are overrepresented in patients. It allows genome-wide mapping with limited resources, but it can generally only map loci into large genomic regions that span hundreds of genes and, despite great success in monogenic diseases, linkage analysis seems to be of limited use in mapping of complex traits. Linkage analysis is based on inheritance of chromosomal fragments within families with affected and unaffected individuals. In principal, there are two approaches to genetic mapping: linkage and association analysis (reviewed in ). This soon led to successful identification of several disease-causing genes, often providing the first information on disease mechanisms. The history of genome-wide mapping of disease-causing genes began in 1980, when linkage analysis by use of anonymous genetic markers was suggested as a method for conducting 'forward genetics' analyses (hypothesis-free mapping starting from a trait of interest).
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