I’m roadtesting personal genomics services, starting with deCODEme, since many of the genotype-phenotype associations they report have been published in a reputable journal. I am the guinea pig and here are the ground rules: I will reveal everything I believe to be useful to future research. If that seems too coy, please comment and I will answer truthfully. I reserve the right to move the detailed discussion elsewhere, since space in Nature Genetics is limited, even in the blog (thanks for the space, Alan, apologies if this seems TMI).
These services offer the opportunity for real people to participate in research and to address for the very first time the question, “I have this genotype, what will happen to me?”. The tests offered are not clinical tests, so insurers, employers, physicians and family, please comment as fellow research participants and don’t try to make more of these information services than they purport to be. By real people, I mean individuals with their own responses and interpretations of the research as it affects them, rather than the anonymized people genetic epidemiology uses to make its predictions.
The first figure below shows my thoughts on the subject before I started to look at the results. My initial impression was that I was not going to pay attention to SNPs that on published precedent suggest my lifetime risk of any condition is less than 30%. I guessed I would research any biological hypothesis in the 30-60% range and possibly seek a clinically approved genetic test and medical advice for any genetic prediction of elevated risk over 60%. Given the predictable response of my fellow commuters to eg. seat belts, anti-lock brakes and airbags, I feared I might compensate behaviorally if I got a hint of protective alleles (eg. ADH2*2, CCL3L1). Impressed by Andrew Niccols’ prescient (if insufficiently palindromic) GATTACA I assumed that there might even be SNPs that would convince Uma Thurman to have my babies.
The first unexpected problem was to identify myself. Since the website is very new and I don’t have the raw Illumina SNP calls or any population samples with which to examine the cluster plots myself, I can’t verify the raw data. Even if I could do so, I have little but consistency with other genotyping services to ensure I am looking at my own genes. From Genographic, I know I have Cambridge mitochondria (H, 16188G, 16311C, 16519C) and a R1b1c Y chromosome and from DNAPrint Genomics’s “proprietary AIMs”, I know only that I am mostly of European ancestry (which luckily tallies with the origins of my great great great grandparents: 12 German, 9 English, 5 Dutch, 2 Irish, 2 Welsh, 1 Swiss, 1 Scottish). Thanks to Daniel Gubjartsson’s recent paper, I also know I am quite likely to have brown hair and brown eyes. The main problem, apart from lack of SNP data to search on my own via Greg Lennon and Michael Cariaso’s wonderful SNPedia site and the underlying literature, is the problem of self recognition.
Individual taste preferences might provide a solution, so I suggested the self-recognition problem might be solved via an olfactory SNP-social-network-wine-club. Another consumer genomics company does report on “taste-related” alleles but they haven’t invited me to the party….. I guess the Icelanders are still running the gas chromatograph on the 70cl of wine the last foreign visitor brought into the country in their duty-free allowance.
Using the information at my disposal, I first plotted my risk ratios against the prevalence of the conditions.
The rheumatoid arthritis results caught my attention since the combination of major and minor contributors and mix of risk and protection alleles pretty typical of the other common diseases for which more than one locus has been implicated. Here are the actual results:
I next tried plotting my risk against the population mean risk, as in my sketch above. A decade of research reveals a several things that I couldn’t have predicted on the back of an index card. My zone of solidarity is – of course- a cone of solidarity, since the variance of the risk increases with the risk.
Seen this way, SNPs associated with larger risks of rarer conditions fall into perspective. So what can I offer Uma? It goes without saying that I wouldn’t kick her out of bed for eating cookies. In the very unlikely event that I were to do so, I would draw her attention to my elevated risk of “restless leg syndrome”. I would not be eating the cookies myself, because of the theoretical worry of type 2 diabetes. Observing a BMI of 27 from a safe distance, she would not be particularly convinced by my predicted genetic chance of resisting the onset of middle-age spread.