Read Here Is a Human Being Online
Authors: Misha Angrist
Here Is a Human Being (18 page)
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Pharmacogenomics is the science of using an individual’s genetics to determine which drug and what dose will be most effective. Medco is a Pharmacy Benefit Manager: it manages the prescription drug (and sometimes other) part of an employer’s health benefits. PBMs try to control administrative costs of processing prescription drug insurance claims and ensuring that beneficiaries are taking the right medications for the right conditions. One can see how genetics might help a PBM by pointing patients to drugs that are more likely to work based on their particular drug-metabolizing gene variants.
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This did not stop 23andMe from returning results on a subset of patented breast cancer mutations, however; the company began offering these results in February 2009; http://www.genomeweb.com/dxpgx/23andme-adds-brca-breastovarian-cancer-testing-service.
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While our genomes are 99.9 percent identical to one another on average, the 0.1 percent still adds up to 3 million differences. And because human populations were geographically separate for long periods of time, it is possible to make fairly precise estimates of someone’s continent of origin based on a few thousand DNA markers. Indeed, this is how 23andMe (see chapter 5) and companies like Family Tree DNA assess their customers’ origins.
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MIT faced a minor insurrection by female faculty members in the 1990s, which resulted in an acknowledgment of gender discrimination and a concerted effort to address it.
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The provost by this time was L. Rafael Reif.
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hanks to the late, great, and supercheap Skybus Airlines, Ann and I could afford to bring the kids to what had become, after only one visit, my favorite meeting: Advances in Genome Biology and Technology, in Marco Island, Florida. As I intimated in chapter 5, AGBT is to DNA sequencing what Macworld is to all things Apple: a highly anticipated annual unveiling of sleek new toys, replete with the requisite back-channel discussions, competitiveness, fire hoses of data, and more than a little showmanship, all at the plush Marriott resort right on the beach.
AGBT could be counted on for theatrics (Pacific Biosciences, still more than two years away from launch, sponsored fireworks over the Gulf) and rumor-mongering (“So and so’s new machine is having problems”). But by 2008, the next-generation sequencing field had gotten more crowded,
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with Illumina having overtaken first-to-market 454 and ABI trying to play catch up after launching only a few months prior to the February meeting.
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Half a dozen other companies claimed to be “close”
to bringing instruments online. Attendees heard big-picture, crystal-ball talks about “the future of DNA sequencing” and more narrowly focused presentations with sexy titles like “Respiratory Bacterial Pathogens Utilize Polyclonal Infections and a Distributed Genome as Population-Based Chronic Virulence Traits.” I confess I skipped that one for some quality time in the Tiki Pool and a few drinks with umbrellas in them.
George was not there in the flesh, but certainly was in spirit. On a late afternoon inside a rented suite at the Marriott stood his lab’s crowning technological creation (at least for the moment): the Polonator. I had already seen the hastily assembled marketing piece, which was adorned with a picture of a large blue box that had been slightly warped in kind of a Daliesque way, a nice design touch and appropriately Churchian. The splashy-cum-nerdy brochure announced the machine’s arrival:
Dover, in collaboration with the Church laboratory of Harvard Medical School, introduces the Polonator G.007, a revolutionary approach to second-generation sequencing. The Polonator G.007 is a completely open platform, combining a high performance instrument at a very low price point … [Users] are totally free to innovate; all aspects of the system are open and programmable… .
[The Church lab’s] vision, as expressed in the Personal Genome Project, the development of the Polonator, and their recent formation of the PGx team [that will compete for the X Prize], is quite simple: to deliver the benefits of second-generation sequencing to the largest possible base of potential users, as quickly and efficiently as possible.
… For those intrepid souls willing to slip into the driver’s seat, the Polonator is completely open and at your disposal. Beyond buckling up, our only request is that you respect the open nature of the Polonator system, and promptly publish (or better yet communicate immediately via our user community forums) any enhancements that you might develop. It is through your creativity that the Polonator system will evolve.
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The Polonator would be more than just a sequencer; it would be a philosophy—a way of life. Like the PGP, this thing was not for the timid. Why this approach, George? “For anything you do on government grants,” he said, “open-source is a good idea. Also, I survived the Applied Biosystems monopoly; I always felt it was too hidden and it was too stifling. I always felt like, ‘Gee, if somebody had the resources, wouldn’t it be great to just have all this stuff in the open?’ I think that feeling comes from having benefited from open-source software myself. And it also seems to be consistent with what we’re doing with respect to the ELSI [ethical, legal, and social issues] aspects of the Personal Genome Project. We are trying to be transparent in every way.”
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Applied Biosystems was the company that won the race to develop automated sequencing in the 1990s. By convincing bad-boy scientist Craig Venter to undertake a private effort to sequence the human genome and compete with the government’s Human Genome Project, ABI became the arms dealer that catered to both sides of the war. Venter and the NIH-sponsored public effort each bought hundreds of ABI’s instruments at three hundred thousand dollars a pop. And with the company’s model 3700 (and its successor, the 3730) installed as the industry standard, ABI could then charge lots of money for reagents: proprietary molecular bullets for the company’s high-tech guns. It was a brilliant move and it helped to keep ABI’s balance sheet deep in the black and its machines entrenched in hundreds of molecular genetics labs for the better part of a decade.
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But now obsolescence was in sight: the wealthier labs had already begun to switch to the new platforms and draw down sequencing on the old machines.
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In 2009, I saw a used 3700 on eBay for about $3,500, shipped. In another auction, its predecessor, the 377, was sold for a winning bid of $99.
In the suite at the Marriott I helped myself to a glass of red wine and inspected the Polonator up close. Even someone who had no idea what it was had to be impressed with the aesthetics. It was electric blue, a much bolder color than any of the competition’s wares. Its glass door was flanked above and below by bands of orange racing stripes. Inside were all of the usual moving parts characteristic of a next-gen sequencer: a robotic platform to cradle the flow cell—that is, the small piece of glass that held the DNA to be sequenced; a charge-coupled device camera to record the images of each base after it was incorporated; and lots of tiny capillary tubes that moved enzymes and other reagents in and out of the flow cell. Next to it was a computer whose job it was to instruct the Polonator. And lo and behold, this Polonator was actually on! Its lights were flashing and its parts humming as they moved stuff from one place to the other. If this thing worked, I thought, I might actually get my sequence someday.
The man who had taken the technology from the Church lab and turned it into an exemplar of sleek design was Kevin McCarthy. Were one to draft a prototypical George colleague from the technology sector, Kevin would probably be pretty close to the final iteration: a tousled mop of gray hair, skinny with a buttoned-down shirt, oversize wire-rimmed glasses. An engineer not entirely comfortable as pitchman but full of ardent belief in his product. An inventor.
A year earlier, McCarthy, who’d been put on to the Church lab by a sales rep, was being escorted to Harvard Medical School to meet with George’s team. But his coworker/driver got lost in the medical school maze. By the time they made it to George’s office, they had all of fifteen minutes to make their pitch. “And it wasn’t like they were dying to see us,” McCarthy said.
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At the time the Polonator was much closer to a science fair project than a commercial product. When I first visited, “Polonator Central” was still a small windowless room within the sprawling Church lab. Inside a boom box throbbed with the Rolling Stones’
Steel Wheels.
The first thing one noticed was the temperature: 18° C, or about 64° F. Ligase, the enzyme used to stitch DNA together in the “Polonation” process, liked it cool; early versions of the Polonator had no onboard refrigeration (or onboard much of anything), so Church protégés Jay Shendure and Greg
Porreca had to keep the ambient temperature down. The room was littered with tangles of black wires connecting microscopes to computers on stainless steel shelves. Space was so tight that the keyboards dangled vertically over the sides; Rube Goldberg would have been proud. Each one of these makeshift arrangements had been named after a character from
The Simpsons.
Marge, I noticed, was in the midst of running a batch of samples. On the screens were thousands of white dots, like stars on an especially clear night. These were polonies—short stretches of DNA that had been amplified millions of times.
“I wandered into the lab and saw some interesting things,” McCarthy recalled diplomatically. “I said, ‘I can do a lot of these things better than this stuff you’ve cobbled together.’ It began with a few core components and just kept getting bigger. I said, ‘Would you like some metal to connect all this stuff?’ Finally it got to the level of, ‘How about we just make the whole thing?’ They were like, ‘Yeah! Let’s go!’”
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Back in the main ballroom, Baylor’s Amy McGuire was making a presentation on the ethical challenges of personal genomics. We were living in an exciting time, she said, but the excitement was tempered by worry. All of the events of the last year or two—the publication of individual genomes, the X Prize, NIH grants meant to hasten the arrival of the thousand-dollar genome, genome-wide association studies, and yes, the PGP—raised some ethical issues that for the most part had not been in play before the digital and genomic ages. Among the biggies:
Did researchers believe their own informed-consent forms and did subjects understand them?
Should research results be returned to research subjects?
How should investigators share data, and with whom?
Projects like the PGP raised the larger question: Can participants consent to uncertainty? To paraphrase Donald Rumsfeld, could we accept not knowing what we did not know? Clearly the ten of us thought we could; we also thought that anyone who was comfortable with the unknown should be allowed to assume those risks. NIH, on the other hand, was clearly
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down with the idea; governments and regulatory agencies liked certainty. McGuire did not take a stand—"All of these approaches have merit,” she said.
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But unlike the rest of us, she had actually walked the walk: she was the one who had navigated the ethical path for the release of Jim Watson’s genome to the world. Watson was, for the most part, like the PGP-10: he was prepared to let it all hang out—to deposit his genome into a public database and let the world have unfettered access to his gene sequences and the rest of his DNA. With one exception.
In the 1990s, scientists at Duke University (disclosure: my employer since 2003) discovered that the apolipoprotein E (APOE) gene was a major risk factor for garden-variety, late-onset Alzheimer’s disease that some 5 million Americans are living with (there are rare, purely genetic forms as well). One copy of the APOE4 version of the gene put you at threefold higher risk of developing Alzheimer’s. Two copies and you were really in trouble: by age eighty-five, more than 50 percent of people with two copies developed Alzheimer’s.
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Would people really want to know if they were at such high risk for a disease they could do almost nothing to treat or prevent?
Watson had made his stance clear in the press and also during our interview at Cold Spring Harbor. “My Irish grandmother died of Alzheimer’s at eighty-three,” he said. “I don’t want to worry that every lapse in memory is the start of something. I’m not afraid of the future, but I don’t want to know. Of course, I could be homozygous APOE4 and still not get Alzheimer’s, so … it’s complicated.”
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Indeed it was. After McGuire’s talk, questioners from the audience lined up in the aisles. Among them was a fresh-faced young man in shorts and a T-shirt. This was Mike Cariaso, who, according to a speaker bio I read for a later meeting, “enjoys travel, skateboarding, reading genomes, and programming in Python.”
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When he got to the mic, Cariaso informed McGuire—and the rest of the audience—that it was possible, and in fact quite easy, to infer Watson’s genotype using his available DNA sequence data from one and/or both sides of the APOE gene.
Geneticists have given this phenomenon the rather unwieldy name of linkage disequilibrium. What it basically means is that even though parts of each parent’s set of chromosomes
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get exchanged when sperm and egg come together (recombination), the process is not entirely random: two genes that are right next door to each other on a chromosome tend to travel together through the generations. Genes that are on the same chromosome but farther apart are more likely to be separated during recombination—they are less tightly linked. In order to prevent Watson’s APOE status from being known, Baylor had redacted or “scrubbed” his APOE sequence and some amount of DNA on either side. But it wasn’t enough. Cariaso was still able to use the more distant sequence: by knowing which versions of the SNPs on either side of APOE Watson inherited, Cariaso could check the genome databases and see what version of APOE tended to travel with the more distal parts of the chromosome that hadn’t been scrubbed. This type of deduction—comparing what’s known in other cases to an unknown case like Watson’s—is how linkage disequilibrium works.
