GINA To The Rescue?

While some see personal genomics as ushering in a new era of personalized health care, it also raises the specter of . Conceivably, health insurance companies could start to consider a positive SNP test for a disease to be a pre-existing condition, for example. Or an employer might not hire someone who carried an increase risk of a mental illness, according to their genetic data. To answer some of these concerns, Congress passed GINA, the , in 2008.

But as Hsu points out, it's only a first step. "As it stands, it only applies to and to employer discrimination based on genetic information. It doesn't currently apply to life insurance or long term care insurance, things that people's decisions might be effected by because of genetic information." He also points out that GINA only deals with the approval or denial of health care coverage, leaving insurance companies and health plans free to charge higher premiums for those they deem risky.

The issue of is particularly complex, according to David Magnus. Imagine that a certain subgroup in the general population is likely to become ill in the presence of some pathogen which is otherwise well-tolerated by people. If there was a test for that variation, a company might very well want to screen potential employees for it, if the work environment would expose the employee to the pathogen. "But then that raises questions about who has the authority to make those decisions," Magnus says. "Can you force that testing on people against their will? If they decided that they needed the job, that it was much better paying than any other job in town, could they decide that it's worth it to get exposed to the risk? These are all the kinds of concerns that people have been very worried about."

Magnus also points out that to deal with this flood of new data. "This is a huge problem, because then what are you supposed to do with this data? If you can't understand it, and a clinician can't understand it, what are we going to do with it? I'm very concerned that people are going to believe that they are at increased risk or decreased risk [for a disease], when they aren't."