Unfortunately, I’ve had a bit of a distracted day today; some analysis that is being presented tomorrow failed, and as a result I dropped off the radar somewhat trying to put it right.
I sat in the “Lessons from High-Throughput Sequencing” session, and picked up bits of it, but was generally distracted. Zam Iqbal presented some very impressive work on assembling genome sequence as diploid individuals, which will be extremely important in the future. The main reason for this is that it allows accurate HLA typing from whole-genome sequencing; HLA typing costs hundreds of dollars, so getting it for free as part of the genome is a major win for personal genomics.
Low-Key Personal Genomics
An interesting, though not new, story came in the form of back-to-back talks by Euan Ashley and Russ Altman on the disease and pharmacogenomic work on Steve Quake’s genome.
People already bring their physicians 23andMe data, and within the next 10 years they will doubtless start bringing whole genome sequences. What can we do with this information? As a pilot, Euan and Russ decided to admit Steve Quake as a patient, on the grounds that he has had his whole genome sequenced already. (Aside: it was sequenced on a the very short-read heliscope, and that, combined with a lack of systematic targeted validation, makes me somewhat wary of the results.)
The story here is relatively neat, and has already been published. Steve’s genome was analysed and a number of very nice visualisations produced (including a brilliant plot of environmental/genetic interactions to help plan lifestyle changes). It was found that he had a high risk of heart disease, as well as an increase and decreases responsiveness to various drugs. It was decided to prescribe Steve with drugs to lower his cholesterol and thus the risk of heart disease.
In this case, the majority of health information came from the lipid screen. Steve’s HDL and LP(a) levels were borderline worrying, and given that he has a family history of cardiovascular disease I think many physicians would have given him something to lower his risk. The additional genomic information was mostly reassurance; he was likely to respond to statins, and was unlikely to suffer side effects.
People like to think about genetic risk in sweeping terms, screening everybody, and using their genetic risk alone to plan their medical future. However, the real power of genetics will be in the type of small-scale, integrated decisions that go on in doctor’s offices every day. My patient has a predicted-damaging coding modification to the target of drug A, so I’ll pick the pretty-much-as-effective drug B. He smokes, and is overweight, but his predisposition to diabetes and coronary heart disease is high/low, so it is/isn’t worth risking the side effects of rimonabant. Genetics integrated into day-to-day medical practice.
