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For the pharmaceutical industries, geneticists, and venture capitalists, the immediate challenge is to find a population that will provide sufficient numbers of disease victims, the clinical data necessary to accurately identify the disease, and the opportunity to take DNA samples from everybody involved. Picking the right population is a choice of trade-offs. The bigger the population, the greater the sample size and the better the statistics, but the more difficult and expensive it becomes to get accurate clinical data. Large extended families will likely share very similar disease-causing genotypes, which makes it easier to identify the relevant genes, but those mutations or gene variants might be specific to the family and rare in other populations.

The effort to achieve the right balance among these trade-offs has led groups to various strategies for setting up and exploiting the information contained in large medical databases. In contrast to Newfound Genomics, some have shied away from looking at closely related populations. Cambridge, MA-based Genomics Collaborative is, for instance, recruiting physicians and letting them enter patients on a disease-by-disease basis. This network is growing at the rate of 7,000 new patients every month, says CEO Michael Pellini. Eventually, he says, the company hopes to have genotype and phenotype data on a half-million patients, representing “large heterogeneous populations.”

This kind of population, Pellini argues, will offer up gene-disease associations-and the diagnostics and pharmaceuticals that might come out of them-with an applicability to large, diverse populations. Pellini cites BRCA1, one of two genes associated with familial breast cancer. When the gene was first identified, he says, “People thought it would be implicated in a very significant number of women with breast cancer. When follow-up studies were conducted to validate that association, it was realized that BRCA1 is actually implicated in less than 10 percent of women with breast cancer. One of the reasons that occurred is the researchers started with small studies and with homogenous populations. Think about it. If you develop a diagnostic that is based on one population, one thing you know is that it’s representative of that one population. You have no idea if it’s representative of any other populations. Our goal is to come out with the diagnostics that are actually representative of a very broad population, and ultimately, to develop therapeutics with the exact same rationale.”

At GlaxoSmithKline, the working philosophy of Allen Roses, who heads the genetics program, is to pick the diseases, recruit the world experts on those diseases, and then let the experts recruit the patients, first from families with a history of the disease, and then from what are known in the lingo as “sporadic” cases-those isolated cases without a family history. GlaxoSmithKline is building eight “clinical genetic networks,” each for a different chronic disease, and Roses estimates that each network will cost $8 million for the first three years. “It ain’t cheap,” he says. “It is not high throughput to work up the data patient by patient, family by family, control by control. It is the part of the study which no technology can circumvent. It is the slowest part. But what you get out of it, if you put in the effort, is the polymorphisms [specific gene variations] of specific genes that are-not ‘could be,’ not ‘might be,’ not ‘we believe’-but are clinically associated with the disease.”

Despite the optimism, the population genomics boom has the potential to become mired in two distinct controversies-one ethical, the other scientific. The ethical debate was ignited three years ago, when former Harvard University neurology professor Kari Stefansson collected $12 million in venture capital and returned to his native Iceland to launch deCODE genetics, with the dream of mining Icelandic DNA for disease-causing genes.

To Stefansson, the Icelandic population represents an incomparable genetic resource. Virtually all the 280,000 inhabitants are descended from the Vikings who landed in the late ninth century. And this inbred population comes with excellent medical records beginning in 1915. As a result, Iceland represents a population in which finding underlying disease-causing genes should be as easy as it gets. Indeed, the potential in terms of new drugs is so great that in February 1998 deCODE signed a deal with the Swiss pharmaceutical giant Roche that could potentially be worth $200 million over five years.

Controversy, however, erupted in the spring of 1998 when the millennium-old Icelandic parliament took up consideration of a bill that would grant deCODE the right to construct a national health-records database of the entire Icelandic population. The bill gave deCODE a 12-year exclusive license to run the database and sell access to third parties, which would include any other scientists who might want to use the records.

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