An inspiring article in Ars Technica describes the case of Kim Goodsell, an endurance athlete who discovered a novel genetic flaw linking her two rare diseases, Charcot-Marie-Tooth disease and arrhythmogenic right ventricular cardiomyopathy (ARVC). Kim spent hundreds of hours teaching herself genetics, enough to read and make use of the extensive research literature at Pub Med. She combed through 40 different genes believed to play a role in her disease, finally honing in on LMNA, which codes for a protein integral to the structure of the envelope around the cell nucleus.
To verify this hypothesis, Kim asked for a complete sequencing of her LMNA gene, at personal cost, and against the advice of her doctors. How did doctors respond to her request?
In November 2010 Kim presented her case to Ralitza Gavrilova, a medical geneticist at the Mayo Clinic. She got a frosty reception. Gavrilova told Kim that her odds of being right were slim. “I got this sense that she thought I’d made an unfounded shot in the dark,” says Kim. “That I didn’t understand the complexity of the genome. That I had been reading the Internet, and they come up with all sorts of things there.”
But as it turns out, Kim was correct — she had an extremely rare mutation in a highly-conserved locus of LMNA. Subsequent academic research corroborated Kim’s unpublished result about the connection between LMNA, Charcot-Marie-Tooth, and ARVC. Although her conditions are (currently) incurable, Kim is taking scientifically informed measures to manage her conditions.
I think this case teaches several valuable lessons:
- Patients are highly motivated, and will go to great lengths to understand their diseases. They have a much greater incentive to spend time and effort on research than any doctor, and we in healthcare must do everything that we can to empower them in their efforts. Anyone with a hypothesis should be able to test that hypothesis, no matter how outlandish or non-intuitive. That is how new discoveries are made.
- Data and tools need to be available to the general public. We are still in the early days of genomic medicine, but genetic data will be collected in increasing volumes and those data need to be accessible to patients. Patients and other non-professionals need to have access to tools that help them make sense of their data. In Kim’s case, a very simple program could have flagged her rare variant as a “variation of unknown significance”. A community of Kims would be even more powerful, allow a researcher (academic or otherwise) to look for correlations between genotypes and phenotypes. I believe we are seeing just the beginning of the potential for crowd-sourced research.
- As more data come online, we need to understand the ethical and privacy requirements for genomic data, and design systems (like Genecloud) that take these factors into account. We must always keep in mind that governance cannot come at the expense of access and utility — we need to remove obstacles to research, not erect new ones. Balancing these concerns is of the utmost importance.
As I think Kim’s case illustrates, the future of medicine is not going to be the exclusive purview of medical professionals, nor is it solely in the hands of those who can bring the greatest computing power to bear. Our best hope for the future lies in connecting the most motivated parties with data and tools that allow them to explore and learn — to give power to the people.