A Numbers Game

A fascinating article in the New Yorker describes the case of Bertrand Might, a child with a novel genetic disorder, and the struggles of his parents to understand and manage their child’s medical condition. The article conveys three critical implications for disease management in the genomic age:

  • Genomic sequencing will be a first step in diagnosing diseases;
  • When a disorder is novel or extremely rare, similar cases are unlikely to be concentrated in one place — they will be geographically dispersed;
  • Collaboration across institutional and geographical boundaries holds the key to successful diagnosis and treatment.

Bertrand Might had health problems from birth, including massive seizures, improperly functioning tear ducts, facial abnormalities, and developmental issues. One by one, diagnoses were proposed and eliminated, until one of Bertrand’s doctors suggested genomic sequencing. Sequencing was very effective in narrowing down the likely cause of disease — two different mutations in NGLY1, one from each parent. However, in the absence of additional comparable cases, Bertrand’s would be an anomaly: one-of-a-kind, isolated, noted, filed away, forgotten.

In the past, researchers might spend years trying to locate a second case of a newly discovered disease, because the dissemination of information was largely based on publication in medical journals and conferences, and on serendipity. While the Internet has radically improved the way research results are propagated and discovered, the system is still little more than a highly efficient version of the machine that has been operating on the same principles since the Enlightenment. We can do better. In an era when systems like Twitter can help to predict uprisings half a world away, we must do better.

Bertrand’s parents, faced with the prospect of losing their son, were determined to find additional cases. Matt Might, a well-known computer scientist — and the publisher of a truly outstanding blog — wrote an essay entitled Hunting Down My Son’s Killer that spread rapidly across the Internet, eventually connecting with multiple patients throughout the world. Today there is an active, engaged community focused on NGLY1 disorders. Where the scientific community failed, the Internet succeeded.

Rare diseases are a numbers game. As the theory of natural selection would predict, mutations that are truly harmful are rare. The chances of any single study or institution encountering multiple cases is miniscule. The key to progress in treating rare diseases, then, lies in collaboration and data sharing.

And yet, there are so many impediments to data sharing. Patient privacy is often cited as a barrier to data sharing — we believe that it is — but privacy can also serve as a convenient excuse. According to Isaac Kohane, a pediatric endocrinologist at Boston Children’s Hospital:

If you want to be charitable, you can say there’s just a lack of awareness about what kind of sharing is permissible. If you want to be uncharitable, you can say that researchers use that concern about privacy as a shield by which they can actually hide their more selfish motivations.

To distinguish the pure from the impure, we must eliminate privacy concerns as legitimate reasons to hoard data. Addressing the privacy problem directly is the ultimate goal of Genecloud. For the specific instance of novel or extremely rare diseases, our model provides an elegant solution:

  • The researcher interested in a potential mutation creates a (simple) program that queries for a mutation being sought;
  • The program is executed as a filter to anonymously screen genomes;
  • If a match is found, consent is sought from the patient (and/or researcher) to share the data;
  • Assuming consent is granted, the seeker is notified of a match.

This approach dramatically reduces privacy concerns: (a) matching is anonymous (b) the seeker is never required to accept or manage any private data (c) matches are only revealed with explicit consent.

As Dr Might has demonstrated by his initiative, the technology required to remake medicine is here. The marriage of advanced technology and healthcare will not always be harmonious, but by balancing the dual imperatives of data access and privacy, Genecloud will help to stack the numbers game in favor of patients.

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