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Gene genie dilemma?
Sometimes in science and technology, we bite off more than we can chew. Other times, it seems like too much, but ends up being like those disgusting eating competitions where people are shoving dozens of hot dogs down their gullets at breakneck speed.
Biting off more than we actually can chew, I think—or at least very nearly too much—was exemplified by the race to be the first to the Moon. I don’t really think the United States quite knew what it was doing at first, but all the same, when it set out to win that race, darned if it didn’t succeed despite the potentially breath-stopping size of the morsel it chose to consume.
Genomics in recent years falls somewhere in between those hot dogs and the moonshot.
That is, I don’t think it’s a bite that’s too much—there is the clear chance to be nourished rather than choked by it—but at the same time, it’s hard getting that bite broken down. Since we busted the “sequencing barrier” with the Human Genome Project, and all the way up to current technologies like CRISPR to edit the genome, we have made huge strides. We are able to do so much more, study so much more, open new therapeutic options…
And yet, the notion in my headline: The gene genie let out of the bottle.
Few want to cram that genie back in because there’s too much value, and I don’t think we need to. However, I think that in the excitement of genomics (from sequencing to editing and everywhere in between), we have come to think it will solve too many ills and make easy things that are (and perhaps should be) really hard.
We have gained the ability to generate so much genetic data that we are sometimes drowning in it. We lack the ability to make sense out of what we’ve extracted. Yes, we do glean important things, but I think researchers and other life-sciences types—and perhaps more so, companies who want to make names for themselves and attract investment—have left the impression that all our diagnostics, all our cures and all our answers are just a gene sequence or gene edit away.
Genomics isn’t going anywhere, nor should it. But it’s not the only game in town, and I would hate to see us get carried away in the genetic excitement and find that we’re slogging through a marsh of data we can’t manage when there were solid pathways on either side of us all along that we overlooked. And for more on that, you need only look to Peter Kissinger’s column in this issue (“Phenotype beats genotype; measurements beat guessing”)—and he’s a lot more knowledgeable than I am on the actual science, too.