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Published online 30 January 2008 | Nature 451, 516-518 (2008) | doi:10.1038/451516a
News Feature
Genome studies: Genetics by numbers
Genomewide association studies are starting to turn up increasingly reliable disease markers. Monya Baker investigates where we are now and what comes next.
Who would have thought that the future of human health would read like a list of car number plates? Last year, a suite of studies1,2,3 pinned an increased likelihood of developing heart disease on some mysterious culprits: seemingly incomprehensible strings of numbers such as rs10757274 and rs1333040. The number sequences, technically known as single nucleotide polymorphisms or SNPs, are located close to one another on chromosome 9.
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It is indeed important to undertake more genomewide disease association studies because they provide the most unbiased means of locating genomic regions potentially harboring the culprit genetic variations. The biological candidate gene-based association studies are just the opposite, i.e., most biased. In addition, these studies are limited to protein coding genes. With changing definition of a "gene", we need to look at the vast amount of non-coding sequences also. Genomewide approach takes care of all that. By throwing unsuspecting genes through statistical evidence, it promises to accelerate the process of understanding biology.
I am working with the Genes, Environment & Health Program at NIH to support efforts to translate genomewide disease association data into useful applications. As the article notes, this is not straightforward. An open meeting at NIH on March 10-11 will attempt to raise and discuss many of the barriers to translation. See http://www.gei.nih.gov/exposurebiology/meetings/genespractice/index.asp for details.