SeriesShaking the tree: mapping complex disease genes with linkage disequilibrium
Section snippets
Genomic approaches to disease association mapping
Genomics is transforming epidemiology, medicine, and drug discovery,1, 2, 3, 4, 5, 6, 7 and attention is being directed towards population-based genetic association studies for complex phenotypes.3, 8, 9, 10, 11, 12 For many complex conditions, the genetic basis of susceptibility to disease, disease progression and severity, and response to therapy has been increasingly emphasised in medical research, with the ultimate goal of improving prevention, diagnosis, and treatment.4, 5, 13, 14
Genomic information in mapping complex disease genes
We are at the beginning of our ability to map complex disease genes. Sequencing of the human genome remains the key to this enterprise, but the focus of that project was the consensus human sequence, which by definition cannot contain information about individual differences of medical relevance.23 To make use of the consensus sequence, the SNP Consortium was formed in 1999, with other public and private projects, with the aim of discovering common polymorphism sites in the human genome.24 The
Methodological and study design issues
Increasingly complete SNP databases, better genotyping, high density LD maps, and large, population samples are essential for complex trait association studies but do not guarantee success. Other obstacles remain,85, 86 many of which are outside the investigator's control. Examples, reviewed elsewhere, include technical issues in genotyping, limitations to our understanding of LD,49, 87 and difficulties in investigating gene-phenotype associations involving multiple interacting genetic and
Whole genome association
High density SNP maps and the identification of genes by the Human Genome Project148 have made whole genome association analyses technically feasible for many conditions.149 However, despite costs heading down to US$0·01 per genotype150 (a target once regarded as highly ambitious), testing all of the 10 million common SNPs would cost at least US$100 000 per individual or US$200 million for a single study of 1000 cases and controls. Exhaustive genotyping for association is therefore currently
The future
Explosive growth in technical capacity and genomic knowledge has been tempered by initial failures to find genes for complex phenotypes using any strategy and our statistical methods and informatics capabilities lag far behind our ability to produce huge amounts of genomic data. What have we learned over the past decade of linkage mapping and association analyses? One important lesson is that everything in human genetics is context specific—specific to the population, environmental exposures,
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