Here Is a Human Being (20 page)

Nor was SNPedia trying to turn a profit like the personal genomics companies. It has been free and open-source from the beginning. It does not perform experiments and it does not offer its own interpretations. It simply mines the literature and reports conclusions drawn by others.

After Marco Island, I got my Affy500 SNP data—five hundred thousand markers—from George and sent it on to Mike. All three of us were gung ho, perhaps a little too much so. George was keen to send it to me because the PGP was still trying to figure out the interpretation part of the equation and he thought maybe I could do some of the legwork to see what was out there. Mike was keen to get his paws on PGP data and anything else people were willing to share—more data points for SNPedia could only help the site to grow and be taken more seriously. And I was jazzed because I would finally get a glimpse of my own genome. Mostly jazzed anyway:

That night Ann and I went out to a benefit dinner. We were going through a rough patch. I was depressed, emotional, and on edge. I was living inside my head, as is my wont, and at that time it felt like an especially ugly place to be. I was feeling paranoid, constantly trying to parse what people said to me, taking every perceived negative, no matter how slight, to heart, and convinced that anything positive that came my way couldn’t possibly be sincere. There’s an old Loudon Wainwright III song that goes, “I wonder why you love me, baby/I hardly love myself at all.”
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This was my theme song. I was sleeping badly. I was angry at Ann, angry at my kids, angry at my therapist, and most of all, furious with myself for being forty-three years old and such a miserable fuckup. Self-loathing was my specialty. As we got out of the car, I told Ann I would be the fourth public genome on SNPedia. She rolled her eyes and asked why. Why did I always have to act so impulsively? I said I thought we had gone over this: that I would be public, that this would be about demystifying DNA for everyone, that we were not our genomes. She didn’t want to talk about it anymore. “I don’t like how we’ve left it,” I said of our discussion. “Sometimes you won’t,” she said.

When we got home I was still in a cantankerous mood; Ann fled to bed. I checked my email and saw that Mike had run my Promethease
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report. With some trepidation I opened the file. As I scrolled through it, I knew I should be clinical, objective. I had been a genetic counselor, for God’s sake. I knew enough about statistics to know that having a risk ratio go from 1 to 1.6 or even 2 meant my absolute risk had only risen from, say, 1 in 10,000 to 2 in 10,000. But still, it was unsettling. And what about conditions where there were multiple alleles in multiple genes—were the risks additive, multiplicative, or something else? Could one bad version of a multiple sclerosis gene undo the health effects of four good versions of other MS susceptibility genes? Was I really likely to get rheumatoid arthritis? Is this why my fingers were always so achy in the morning?

I was drunk, tired, and now fairly certain I was going to succumb to autoimmune disease in the coming months. I began bombarding Mike with questions:

I wasn’t even
trying?
Ouch. Even if that were true, in the genetic counseling handbook, saying that to someone—even someone as irrational as me who ought to have known better—was a huge no-no. How dare he! With the click of a mouse I had gone from an ordinary neurotic/depressive who didn’t believe in genetic determinism to a quivering mess who “knew” himself to be a ticking time bomb. The person most likely to talk me off the ledge was both fed up with me and, incidentally, asleep down the hall. Meanwhile the guy on the other end of the screen had had enough, too. My blasé attitude was being tested. We were at the first of many “what in the name of Gregor Mendel does this all mean?” moments. For all of the hundreds of studies that had been done on tens of thousands of research subjects with and without various diseases, the truth was, nobody knew an individual’s risk for complex diseases with certainty.

It was 1
a.m.
I could hear all of the naysayers at the
New England Journal of Medicine
laughing at my mini-eruption of angst.
You were so sure that this information was harmless. How does it taste now, Genomeboy?

I called Dietrich Stephan. “I think I’m ready to take you up on your offer of a freebie,” I said. “That’s great,” he said. “I’ll get a kit in the mail to you.”
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A few days later I received a “spit kit,” which was basically a tube I was to fill with saliva.
For best results, collect your sample just before eating a meal and when you are in good health… . To make more saliva, close your mouth and wiggle your tongue or rub your cheeks.
Although I was someone who still drooled when he played the guitar, I found that this took a bit of doing. After a few minutes I reached the fill line. I put the plastic tube in the Styrofoam box and sent it off to Affymetrix, the California DNA-chip company that was processing Navigenics’ samples.

In a couple of weeks I received an email that my “HealthCompass Profile” was ready. I didn’t rush to look at it. After my semidark night of the soul with SNPedia I didn’t want to barrel through the process this time. After work that day I dithered around, ate dinner, put the kids to bed. When my inbox was finally empty and I had sedated myself with a full thirty minutes of
Puppy Bowl IV
on Animal Planet, I figured it was time. I logged on.
Welcome! Your results are ready!
Genetic counselor Elissa Levin’s smiling face was there to reassure me. The conditions were divided by “estimated lifetime risk”: = 1 percent, 1 percent–10 percent, 10 percent–25 percent, 25 percent–50 percent, and > 50 percent. Each condition had its own box containing the disease name, my results, and the average lifetime risk for males. If the box was orange, I might want to pay closer attention because that meant either my risk was 20 percent or more above the population average, or my lifetime risk was greater than 25 percent. I was beginning to feel nervous despite myself. My palms were sweaty.

Alzheimer’s was first. This was APOE, the gene Watson and Pinker didn’t want to know. If I had one or two copies of APOE4, I’d be at higher risk. At the time, Navigenics did not test directly for the APOE gene, but rather a marker near it. This was partly for technical reasons and partly because the APOE gene was patented (we’ll revisit this notion). But the marker near it was a nearly perfect proxy for APOE. So did I have one copy of APOE4? Two? I clicked … zero. Navigenics said the average lifetime risk of Alzheimer’s for males was 9 percent, which sounded about right; my risk, given my APOE status, was 5 percent. I felt a palpable sense of relief and a little guilty for allowing myself to feel that. But the fact that I had zero copies of APOE4 meant each of my parents could have no more than one copy. I wanted to call them and tell them, even though that would have been a deterministic thing to do.

Celiac disease: average risk was 0.06 percent; mine was 0.02 percent. Woo-hoo. Bring on the gluten.

Colon cancer: average risk was 6 percent; mine was 5 percent.

Crohn’s disease: average risk 0.58 percent; mine was 0.37 percent. This was based on my genotype at nine different genes.

Type 2 diabetes: average risk was 25 percent; mine was 32 percent. Whoops—time to lose weight, exercise, and maybe get a glucose-tolerance test. As if I didn’t know.

Glaucoma: average risk was 1.1 percent; mine was 3.4 percent.

Graves’ disease: Population risk = 0.55 percent; me = 0.93 percent.

Myocardial infarction (heart attack): Population risk = 42 percent; me = 38 percent. Wow … it was staggering to think that the average lifetime myocardial infarction risk in males is 42 percent. My paternal grandfather died of a heart attack at age fifty; my dad had one at age sixty, as did my mom’s mother. This was another obvious message that I needed to exercise, watch my diet, control my cholesterol, etc. What a shame: I had so wanted to take up smoking.

Lupus: Population risk = 0.03 percent; me = 0.01 percent.

Age-related macular degeneration: Population risk = 3.1 percent; me = 1.1 percent. My grandmother had it. I wondered what that did to my risk.

Multiple sclerosis: Population risk = 0.30 percent; me = 0.17 percent. But this was based on just three markers. MS risk was mediated by dozens of them.

Obesity: Population risk = 34 percent; me = 36 percent. Does this genome make me look fat?

Rheumatoid arthritis: Population risk = 1.1 percent; me = 2.8 percent.

Restless legs syndrome: Population risk = 4 percent; me = 4.3 percent.

Psoriasis: Population risk = 4 percent; me = 2.5 percent.

Prostate cancer: Population risk = 17 percent; me = 12 percent.

These were interesting numbers, but they didn’t rock my world. By now I had gotten a grip. My biggest concern was about metabolic syndrome,

basically a group of risk factors for heart disease: obesity, bad lipid numbers, high blood pressure, insulin resistance, etc. Two years earlier I had been in an exercise study because I was already known to be at high risk for this stuff and I had a modest history of diabetes in my family.

Now I could hear the geneticists saying, “We told you so,” for another reason. Navigenics’ service was fast, efficient, thorough, and impeccably designed and presented. Its explanations of genetics were simple and clear without being condescending. But there’s no way I would have spent $2,500 (the cost in 2008) on it. The problem of course was not that the information was useless; it was that genes told only part of the story of one’s health and so far we were only a few chapters into a very long and complicated tale. Thus, until we started linking environment (as a child did I have lead paint in my house?), phenotype (how much did I weigh?), and lifestyle (what did I have for breakfast?) with personal genomic profiles, it was not realistic to expect that the latter would tell us things that would save—or even dramatically improve—our lives.

That said, in the wake of my genome scans, I began to see my iconoclastic doctor more regularly, I went back to the gym, and I became an aspiring vegetarian for a while (Chinese pork buns were still my weakness). Eventually, with the help of my kids, I got into the Wii Fit. Is this because I worshiped in the Temple of the Gene? No, it’s because the genetic evidence reinforced the story told by my family history: I was at risk for heart disease. Getting my genome done and collecting my medical records for the PGP was a convenient excuse to begin to get my cardiovascular act together.

To its credit, Navigenics constantly updated its results based on the latest science. A year after I received my initial analysis, my risks had changed for many of the conditions, albeit not very dramatically. And where there had been seventeen diseases before, by 2010 there were twenty-seven. I learned that my risk for osteoarthritis, for example, was a whopping 56 percent based on two genes. I clicked on the button that read “What you can do.” Early detection was a good idea, Navigenics said, in order to distinguish joint pain from other forms of arthritis such as rheumatoid arthritis. X-rays, MRIs, and a variety of blood tests might be in order. To prevent it I could lose weight—this seemed to make a big difference as to whether one developed osteoarthritis in one’s knees. Other things to consider, the site said: rubber-soled shoes, no high heels, regular exercise.

This was largely common sense, of course. Osteoarthritis, it seemed to me, was simply collateral damage that came with getting old. One could understand why a customer might peruse her results and recommendations and say “meh.” Meanwhile some geneticists and ethicists had started to complain that these tests would lead to a “raid on the medical commons.”
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In other words, with their genomic results in hand, otherwise healthy folks would begin availing themselves of every medical test they could. The high-tech genome scan would demand a series of high-tech fixes. Genome scans would be the new CT scans—sexy but imperfect and usually unnecessary. And this would place an additional burden on the health-care system and drive up skyrocketing insurance premiums even further.