There have been a whole series of interesting blog posts, news stories, and research articles associated with personal genomics lately that I have been meaning to write about but simply have not had the chance. So instead I am going to try to mash them all together into something meaningful here.
To begin, there is a piece worth reading from Russell Brandom writing at The Awl, expressing his frustration with what he learned, and more importantly did not learn, from his own experience with personal genomics:
Instead of dramatic scientific breakthroughs, the most successful outgrowth has been a crop of VC-fueled personal genetics companies. The concept is simple: for a fee, they’ll tell you everything science knows about your genes.
Brandom goes on to review his own person findings from 23andme, one of the more successful genomics companies:
All of which means that, for $200 you can send off a tube of spit to a 23andme lab in California and get access to a website with literally thousands of statistics about your genome, each somehow just a little short of being a useful fact. A few examples, from my own results.
— My odds of heroin addiction are 2.9x higher than average. It’s hard to know what this means: do I get a bigger kick out of opiates, or a smaller one? The finding is based on a Swedish study from 2004, but on the results page, 23andme also helpfully links to a 2006 study that they list as “contradictory,” so maybe it doesn’t mean anything at all.— I’m a carrier for hemachromatosis. This actually is useful to know. 3% of the population are carriers for a genetic disorder of one kind or another, often something terrifying and degenerative like PKU or Gracile. But not me. I just have the possibility of extra iron in my blood, which hopefully (hopefully!) some doctor would have told me about at some point anyway.
— I have a 33% higher risk of rheumatoid arthritis. It’s hard to know what this means. This figure is derived from a group study, showing that people with this gene (my gene) suffer rheumatoid arthritis at a rate of 3.2% instead of 2.4%. That may mean a lot to an insurance actuary, but for a single person, it comes close to nonsense. If I lived one thousand times, I would suffer arthritis in 32 lives instead of 24—a useless, maddening idea. I won’t live a thousand times. I have only one body and only one life. Either it will happen or it won’t.
In Brandom’s view (and many others), the genome is a massive palimpsest of complexity, that can be represented as data, but from a personal standpoint is something far short of knowledge.
So when sites like 23andme try to lay out all that messy, incomprehensible data for mass consumption, they’ve got quite a problem on their hands. They don’t have any straightforward truths to offer users, just a flood of vague and often frightening ambiguities. But wherever there’s a gap between what they promise and what they can deliver, 23andme fills it with social media. The site’s full of Like buttons, Share buttons, disease groups, Foursquare-style research badges, and comment boards, ready to answer (or at least listen to) any question.
Daniel MacArthur, a geneticist and blogger for GenomesUnzipped, responds, in part, to these complaints:
In general, you should buy a 23andMe test assuming that you will learn some interesting things about genetics and yourself, but nothing that will profoundly change your healthcare or lifestyle.
Of course, that’s not always the case. A small but non-zero fraction of the population will in fact uncover directly useful information: a high lifetime risk of breast cancer, for instance, that (once confirmed by a clinical-grade test) warrants additional screening for early signs of disease.
But the real backbone to MacArthur’s argument is in his closing lines:
There is some truth to the claim that the personal genomics industry has created unrealistic expectations about the value of their product. But that absolutely does not mean that the real value of a 23andMe test is zero. Rather, the value depends both on who you are and how prepared you are to take the time to learn from the information available.
Both writers have it right, but both also highlight the challenge of marketing personal genomics to the masses. For most of the people outside of genetics research or related fields, genetics is synonymous with “science” and perhaps “hard” in an academic sense, but not complex. For most people, genes are things that produce physical traits we can see and measure and touch and comment on. It takes a lot of “cool science” and “technology” to see what those genes are, but once found, they have clear meaning.
Obviously people are wrong in their assumptions.
Consider another recent article by Mara Hvistendahl, published in Slate, titled, “Will Gattaca come true?” (Gattaca being a reference to the wonderful 1997 film starring Ethan Hawke, Uma Thurman and Jude Law):
Natera is one of several companies vying to commercialize fetal DNA tests, or noninvasive prenatal diagnosis (NIPD). A few years ago, a handful of these companies began offering NIPD to determine fetal sex and detect Rh-factor incompatibility—left undiagnosed, a woman with Rh-negative blood carrying an Rh-positive baby can produce antibodies that attack the baby’s blood cells. Recently, we’ve seen a new wave of NIPD applications: Beginning last fall, the San Diego-based company Sequenom rolled out tests for Down syndrome and Trisomies 13 and 18, and Silicon Valley-based Verinata entered the market with tests for the same conditions in March. Rabinowitz expects Parental Support to be available by the end of the year.
The article provides an interesting account of the development of NIPD technology. And in one sense, the world of Gattaca has already become a reality (particularly relative to when the movie was first released 15 years ago). Prenatal screening is already common in parts of the world and, despite some very difficult moral questions around its implementation, is only likely to become more common as we move forward. The basic appeal is the same as was present 100 years ago during the heyday of the early Eugenics movement – if you have knowledge, including knowledge about heredity, why not use it? Why would you intentionally act counter to what you know? In the film, this sentiment is expressed brilliantly by Blair Underwood, playing the role of the “local geneticist.”
The challenge is, as I have said before, data does not equal knowledge. Knowledge requires the filtering of data into something that is meaningful and can inform decision making processes. And most of the personal genome data that is available now simply is not yet at that point.
As another strand of this discussion, check out this recent criticism of Henry Louis Gates Jr.’s show, “Finding your roots,” by Razib Khan at Discover:
From what I can gather Gates regales his subjects with their DNA results, and tells them their ancestral quanta fractions. Nothing too amazing. But it seemed clear to me that when Gates referred to “European”, “Asian” and “African” ancestors, he was communicating to the audience that these quanta really represented those exact populations!
I assume that the geneticists Gates works with explained to him the falsity of this typology.
There are reasons for the public’s general ignorance of how genetics works that go beyond poor media coverage. A large part of the problem, and this informs the poor journalistic coverage of the field, is a systemic problem brought about by the nature of knowledge production within the field. The easiest things for geneticists to clearly identify are the simplest ones…those rare mendelian traits. Indeed, most of our knowledge about genomics until quite recently was focused on mendelian traits. But we now know, because of a huge number of genome-wide association studies (GWAS) and other genomics work, that the vast majority of genetic variation does not come in the form of mendelian traits. Most of it comes from large networks of genes that individually have small effects. And this says nothing about the complexity of epigenetic influenced expression patterns or dynamic environmental feedback systems.
Brandom, in his piece, cites Misha Angrist, author of Here is a Human Being, as saying that the most relevant symbol for the genome is a massively intertwined hairball. In a similar vein, our knowledge of the genome can be described as something like our knowledge of the nature of the universe and astrophysics. Most of our knowledge, like that of early astronomers who could only observe the brightest stars, comes from the easiest to identify genes and associated effects. The development of technology over the past three decades has given us the ability to see far deeper into the astronomical depths of the genome and have given us a massive increase in data, but the nature of the data, unlike those mendelian traits, is complex. The process of turning it into scientific knowledge is slow. So even from within the field, where we recognize the worldview of genomics must be extremely nuanced (and you can see my analogy embedded within a recent American Journal of Human Genetics paper by Doron Behar et al. titled “A “Copernican” Reassessment of the Human Mitochondrial DNA Tree from its Root”), there remains a lack of understanding of how it all fits together and constraints based on what specific studies have been funded, carried out and published.
So what does it all mean? One of the things it means is that this is an area that is crying out for anthropological investigation on multiple fronts. First, one part of the complexity of turning genes into traits is understanding the history of those genes and how they have been impacted by evolutionary forces throughout human prehistory. This is an area for genetics, archaeologists and physical anthropologists to work together on. Second, another part of the same complexity comes from the differential expression of genes in different populations and environmental situations. This is again an area for physical anthropologists, human biologists and practicing clinicians to explore in the context of field-based, cross-cultural studies. Third, there is a huge need to understand how the public turns genomics information into knowledge. Genomics is, as the reference to social media above highlights, about to become a massive cultural meme. Whether the data of personal genomics has become scientific knowledge or not, people will turn those data into personal knowledge. People will make decisions about themselves and others that incorporates their own understanding of what genomics means. This is a huge area that requires the interaction again of practicing clinicians, physical anthropologists and cultural/medical anthropologists.
I am now more than 1700 words into this and I have only covered about half of my intended area, so more will have to come later.
